Using an Integrated Ontology and Information Model for Querying and Reasoning about Phenotypes: The Case of Autism
|
|
- Aldous Hines
- 5 years ago
- Views:
Transcription
1 Using an Integrated Ontology and Information Model for Querying and Reasoning about Phenotypes: The Case of Autism Samson W. Tu, MS, Lakshika Tennakoon, RMP, MSC, MPhil, Martin O'Connor, MS, Ravi Shankar, MS, Amar Das, MD, PhD Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA ABSTRACT The Open Biomedical Ontologies (OBO) Foundry is a coordinated community-wide effort to develop ontologies that support the annotation and integration of scientific data. In work supported by the National Database of Autism Research (NDAR), we are developing an ontology of autism that extends the ontologies available in the OBO Foundry. We undertook a systematic literature review to identify domain terms and relationships relevant to autism phenotypes. To enable user queries and inferences about such phenotypes using data in the NDAR repository, we augmented the domain ontology with an information model. In this paper, we show how our approach, using a combination of description logic and rule-based reasoning, enables high-level phenotypic abstractions to be inferred from subject-specific data. Our integrated domain ontology information model approach allows scientific data repositories to be augmented with rule-based abstractions that facilitate the ability of researchers to undertake data analysis. INTRODUCTION Recent studies have reported an increased prevalence of autism spectrum disorder (ASD). 1 To advance research in identifying common genetic or other factors that influence the etiology of ASD, the NIH established the National Database for Autism Research (NDAR) ( The goal of NDAR is to provide investigators a public resource for collecting, archiving, retrieving, sharing, and analyzing data on autism. A central function of NDAR is to store and to link genetic, clinical, imaging, and other data on subjects who participate in NIH-funded autism research studies. The underlying architecture uses a federated data repository based on the Biomedical Informatics Research Network (BIRN) Grid ( One of the functionalities of NDAR is to provide a query tool to construct data sets for answering specific questions relevant to autism researchers. A question such as Use head circumference to categorize macroencephaly. Then see if the subjects differ in their ADOS and ADI-R cognitive and language profiles, and in their genetic data. requires that phenotypic abstractions (e.g., macroencephaly) be inferred from available data collected from standard autism assessment instruments (e.g., the Autism Diagnostic Interview-Revised (ADI-R) 2 and the Autism Diagnostic Observation Schedule (ADOS) 3 ). Performing such reasoning on subject-specific data in NDAR requires the integration of an information model representing research and clinical data about study subject with an ontology that defines the terms and relationships in the domain. Ultimately, the use of such a combined modeling approach can allow a researcher to formulate a query at the conceptual level, using terms and relationships from the ontology, and have it translated automatically to specific queries that take into account the schemas and source vocabularies of the underlying data sources. The BIRN Grid does not currently address the need to query phenotypic abstractions. It consists of tools, including a mediator and an infrastructure, to handle all phases of the data integration process, such as registration of sources, registry queries, and semantic data queries. 4 The mediator supports a form of semantic data querying where a user can annotate data sources, views, attributes, and attribute values with terms from ontologies. To perform a query, a user can submit a list of keywords, using terms from ontologies available in BIRN. A mediator can then search for these terms and produce a ranked list of relevant sources and relations. A user can request data from individual views generated for each candidate source or from joined views. To develop the ontology of autism that supports the querying of phenotype abstractions in the BIRN Grid, we need to extend the ontologies currently supported in that environment. The BIRN community has developed BIRNLex, a controlled lexicon for neuroscience that can be used to annotate BIRN data sources ( Developers of BIRNLex have adopted and refined practices for ontology development being promoted by the Open Biological Ontologies (OBO) Foundry. 5 Part of these practices is the reuse of existing ontologies covering domains of interest, such as the Basic Formal Ontology (BFO), the Ontology for Biomedical Investigations (OBI), and the Phenotype and Trait Ontology (PATO). The BFO is a foundational ontology that provides a set of upper-level distinctions shared by all OBO foundry ontologies. 6 It promotes a realism-based approach to ontology modeling, which holds that classes in an ontology are universal categories of objects that represent things and processes in reality. PATO, for example, models phenotypes as qualities and dispositionsboth AMIA 2008 Symposium Proceedings Page - 727
2 classes in BFOthat inhere in organisms, which are bearers-of such phenotypes. Our task is to formulated the ontology of autism for NDAR as an extension of the BIRNLex ontology. However, the extension cannot be merely addition of autism-related terms and relationships. We have found that the use cases for the autism ontology extend beyond the capabilities currently supported by BIRN, because the BIRN data integration environment conceives of an ontology only as a network of typed nodes and relations. 4 The research questions addressed in this paper include: 1. How to formulate terms and definitions used in studies of autism as extensions of the BIRNLex ontology and, when appropriate, as PATO phenotypes? 2. How can the structure of clinical and research data be reflected in the ontology so that the formulation of analytical questions are informed by available data? 3. How can abstractions defined in terms of clinical and research data be incorporated into the ontology and related to terms in the literature? METHODS To gather terms, relationships, and abstractions for building our autism ontology, we conducted a literature search and reviewed the data dictionary codebook used by NDAR. Our literature search of the PubMed database used the key words (ADI-R or ADOS or Vineland) and (genes or genetics) and autism. We found 43 published research papers as of March 1, We selected only 26 papers as relevant based on the inclusion criteria of studies who enrolled subjects with a diagnosis of autism and were published in the English language. We supplemented the corpus with standard sources on autism diagnosis, such as the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 7 We then examined the data-analytic requirements of investigations reported in the papers, focusing on the types of terms and relationships that would be needed to retrieve and abstract a data set for the analysis. From NDAR, we obtained a codebook specification of the data elements and their format in the data repository (available at in MS Excel spreadsheets. We manually extracted terms and their definitions from the literature corpus and modeled them as extensions of the BIRNLex ontology in Protégé, an ontology-editing tool that supports the Ontology Web Language (OWL). 8 OWL is the description-logic-based language for constructing ontologies endorsed by the World Wide Web Consortium (W3C). We wrote scripts to import the NDAR codebook data specification into Protégé OWL. To represent definitions and mappings that specify data abstractions and their relationships to other terms in the ontology, we used Semantic Web Rule Language (SWRL), 9 which allows using rules as additional axioms in an OWL ontology. Furthermore, a query extension to SWRL allowed us to specify, using terms and relationships in the ontology, how to extract data for statistical analysis. RESULTS The autism ontology integrates (1) an information model that represents research and clinical data; (2) terms and relationships specified in the domain of interest; and (3) data abstractions that relate observable data with research and clinical terms. To demonstrate the development and use of the autism ontology, we provide illustrative examples of how the abstractions used in a publication by Hus and colleagues (Hus2007) 10 and the terms used in a fragment of the DSM-IV definition of autism are modeled in our autism ontology. We also show the use of the ontology in abstracting and retrieving data needed for performing statistical analysis in Hus2007. Hus2007 characterizes autism phenotypes based on language acquisition, restricted and repetitive behaviors, and savant skills. The phenotype trait for the acquisition of first word, for example, is based on ADI-R item 9 ( Age of First Words ) and categorized as follows: NDW (not delayed words): acquired words 24 months DW (delayed words): acquired words > 24 months NW (no words): no words at time of ADI-R assessment The statistical analysis presented in Hus2007 correlates the phenotype categorizations of individual subjects with their verbal and nonverbal IQ, age, and ADOS and ADI-R domain scores. We next show how data for such statistical analysis may be formulated using the terms and relationships from the ontology. The DSM-IV diagnostic criteria for autistic disorder, in part, says that the subject should have (A) qualitative impairment in social interaction, as manifested by at least two of the following: 1. marked impairments in the use of multiple nonverbal behaviors such as eye-to-eye gaze, facial expression, to regulate social interaction (B) qualitative impairments in communication as manifested by at least one of the following: 1. delay in, or total lack of, the development of spoken language AMIA 2008 Symposium Proceedings Page - 728
3 Figure 1. The representation of data collected through the ADI-2003 autism assessment instrument as part of the autism ontology. First we extended the BIRNLex ontology s informationcontent entity, currently populated with Narrative object, such as Book, Data object, and bibliographical database, with an Assessment result class that represents results of study assessments done on subjects, such as instrument, imaging or genetic testing. Using a Python script, we imported the NDAR data specification as subclasses of Assessment result. Thus data collected through the use of the ADI-2003 instrument, for example, can be seen as instances of the ADI-2003 class, where properties such as acqorlossoflang_aword represent the assessed value of an ADI-2003 item (i.e., age at which first word is uttered) (Figure 1). Because all subject data submitted to NDAR are de-identified and are referenced instead by an NDAR GUID (Global Unique Identifier), it will be possible to join the data across multiple types of assessments. We use OWL s capability to define super-property and sub-properties to classify the items of assessment instruments into domains. For example, the acqorlossoflang_aword property is a sub-property of the Acquisition and Loss of Language and Other Skills domain in the ADI instrument. The property hierarchy allows us to query for relationships at multiple levels of abstraction. We model the Status of age of word as an OWL class defined by the necessary and sufficient condition of being the disjoint union of its Delayed word, No word, and Not delayed word subclasses (Figure 2). We annotate the Status of age of word class with the bibliographic citation where the phenotype trait is defined. Each of the phenotype values, such as Delayed word, is defined in terms of the underlying assessment result using a SWRL rule (Figure 3). The SWRL rule makes use of the Assessment_result information model described previously. Specifically, it says that if the acqorlossoflang_aword value (represented by the variable?wordage) of an ADI 2003 assessment Figure 2. The representation of the Status of age of words phentotype group as a OWL class partition by the possible statuses. (represented by the variable?assessment) is greater than 24 (months), then the human (represented by the variable?subject) whose subject id is that of the assessment is the bearer-of Delayed_word. In this example, we use a SWRL greater-than built-in (a method for extending the capabilities of SWRL) to perform the comparison of an assessment value with a cut-off. The Protégé implementation of the SWRL language allows the use of mathematical expressions, temporal comparisons, and terminological reasoning. The definitions of the savant skill trait, for example, requires averaging of multiple assessment scores, which cannot be done in OWL alone. SWRL rules, like the one shown in Figure 3, are abstraction rules that, based on statements made in the information modelassessment results in the format of NDAR data modelinfer assertion about some quality of study subjects. Transformation of the assertion as data input for statistical analysis requires a further step. Instead of using a logical formalism to represent assertions, we need to represent the qualities such as Delayed word as the value of a variable. We can easily do that by augmenting the ADI information model with attributes like age_of_word_status that has coded values (e.g., 0 for No word, 1 for Not delayed word, and 2 for Delayed word). A SWRL rule similar to the one in Figure 3 can assert that, for a subject who is the bearer of Delayed word quality, his ADI 2003 assessment age_of_word_status attribute is 2. Once the phenotype abstractions have been turned into data values, we query them as part of the available data set. Using an SQL-like extension of SWRL we have developed within Protégé, 11 we can formulate the query constructing the data set for correlating phenotype groups with verbal and nonverbal IQ, age, and ADOS and ADI-R scores in terms of the augmented NDAR data model. ADI_2003_result(?assessment) & acqorlossoflang_aword(?assessment,?wordage)& swrlb:greaterthan(?wordage, 24) & subject_id(?assessment,?subjectid) & orgtax:human(?subject) & subject_id(?subject,?subjectid) birn_obo_ubo:bearer_of(?subject, Delayed_word Figure 3. A SWRL rule concluding that a subject has 'Delayed word' AMIA 2008 Symposium Proceedings Page - 729
4 Figure 4. Partial hierarchy showing the autism-related developmental capabilities The second part of our results concerns the formulation of autism phenotypes in terms of the PATO ontology of qualities and dispositions. Delayed is a PATO quality for occurrence. The status of Delayed word can be formally decomposed as Delay in the onset of the capability to use words, where capability to use words is a kind of developmental capabilities, and onset is the time of a developmental capability's occurrence. Terms used in DSM-IV diagnostic criteria for autism can be modeled in exactly the same way as the decomposition of phenotype traits. By creating an ontology of developmental capabilities, such as the one shown in Figure 4, we can define dispositions toward autisms in terms of PATO qualities of the developmental capabilities. For example, qualitative impairment in social interaction can be defined as the PATO quality impaired of some Social_interaction developmental capability. Because of the subsumption hierarchy of developmental capabilities, any assessment of, say, impaired eye-to-eye_social_interaction, will be classified as an impairment of social interaction. Using the OWL 2.0 s description logic capability to define qualified cardinality restriction, we create OWL classes that represent criteria like qualitative impairment in social interaction, as manifested by at least two of the following as assessment results where there are at least two instances of impairment of social interaction. Based on an information model of assessment result, we can represent the DSM-IV diagnostic criteria depicted in the sample text quoted earlier as necessary and sufficient conditions for inferring the presence of autism. DISCUSSION Most of the existing works on the use of ontologies to facilitate data integration focus on the annotation of data, images, and literature with terms from ontologies. 12 In this paper we described a modeling approach that extends the use of ontologies by integrating them with information models so that inferences can be made with the data themselves. While we have established the feasibility of combining such reasoning with data queries to derive data sets to be used in statistical analysis, we do not expect autism experts will be able to write OWLbased rules and queries themselves. In work parallel to that reported in this paper, we are trying to find patterns that would allow us to design templates that can ease the task of writing such abstraction rules and queries. We found that BIRNLex and PATO provide an adequate framework for specifying the qualities and dispositions that represent phenotypes described in the autism literature. Nevertheless, we found that OWL does not allow a direct description of a subject bearing a phenotype if the relationship between the subject and the phenotype needs qualifications. Instead, such descriptions could be represented as statements in an information model. The BFO and PATO s realism-based principle of modeling relations between real-life entities is problematic when we want to extend the model to state that a subject is the bearer-of a quality during certain time. In this case, the bearer-of relationship is an ternary relation involving a subject, the phenotype quality, and time. OWL, like other entity-attribute-value (EAV) languages, allows only unary (class) and binary (property) relations. As noted by Mungall, 13 OWL does not permit the direct representation of an assertion saying that a subject is the bearer of a quality during certain time. The alternatives that Mungall considered were judged unsatisfactory. The standard method to represent n-ary relationships in an EAV language is to reify the relationships as objects. 14 Our approach of integrating an information model of AMIA 2008 Symposium Proceedings Page - 730
5 assessment results with an ontology provides such a mechanism. Instead of modeling a subject as the bearer of a phenotype, and not being able to state the temporal extent of the relationship, we model the assertion as a statement in the information model. Thus, for example, we can create a phenotype-description entity in our information model. Similar to an assessment result, it has a subject id, the qualitative or quantitative phenotype value, the time interval during which the assertion is valid, and any other contextual or qualifying information. Our current implementation relies on a SWRL/database integration that fetches the necessary data into memory for rule and query processing. 11 For large data sets, a more scalable architecture is needed. It may be possible to treat the SWRL rules and OWL class expressions as specifications that can be translated into more conventional database triggers and queries. Another possibility is to precompute and store abstractions so that they are readily available for querying. Our work to construct an autism ontology so far focuses on solving the modeling of terms to conform to and extend the existing BFO and BIRNLex ontology development framework. In contrast, Petric and colleagues 15 used machine-learning and text-mining techniques to construct ontologies of the autism domain. Using the semi-automatic tool OntoGen ( they constructed the ontologies as hierarchies of terms, and used the underlying document corpus to discover suggestive relationships among terms in the ontologies. Such semi-automated machine-learning approach can very usefully supplement the labor-intensive work that our manual ontology development entails. Acknowledgement This work was funded in part by an NIMH supplement to the Protégé resource funded by NLM grant LM The authors thank Lynn Young, Bill Bug, Dan Hall, and Matt McAulliffe for discussions and assistance on this project and Mor Peleg for her extensive comments. REFERENCES 1. Rice, C.E., et al., A public health collaboration for the surveillance of autism spectrum disorders. Paediatr Perinat Epidemiol, (2): p Lord, C., M. Rutter, and A. Le Couteur, Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord, (5): p Lord, C., et al., The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord, (3): p Astakhov, V., et al. Semantic Data Integration Environment for Biomedical Research. in Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems p Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, (11): p Grenon, P., B. Smith, and L. Goldberg, Biodynamic Ontology: Applying BFO in the Biomedical Domain, in Ontologies in Medicine, D.M. Pisanelli, Editor. 2004, IOS Press: Amsterdam. p American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders DSM-IV-TR O'Connor, M.J., et al. Supporting Rule System Interoperability on the Semantic Web with SWRL. in Fourth International Semantic Web Conference Galway, Ireland. 9. Horrocks, I., et al. SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Member Submission 21 May [cited 2008; Available from: Hus, V., et al., Using the autism diagnostic interview-- revised to increase phenotypic homogeneity in genetic studies of autism. Biol Psychiatry, (4): p O'Connor, M.J., et al. Efficiently Querying Relational Databases using OWL and SWRL. in The First International Conference on Web Reasoning and Rule Systems Innsbruck, Australia: Springer. p Louie, B., et al., Data integration and genomic medicine. J Biomed Inform, (1): p Mungall, C., et al. Representing Phenotypes in OWL. in Third International Workshop of OWLED Innsbruck, Austria. 14. Noy, N. and A.L. Rector. Defining N-ary Relations on the Semantic Web [cited 2008 June 17, 2008]; Available from: Petric, I., T. Urbanicic, and B. Cestnik, Discovering Hidden Knowledge from Biomedical Literature. Informatica, : p AMIA 2008 Symposium Proceedings Page - 731
An Ontology-Based Approach for Computational Phenomics: Application to Autism Spectrum Disorder. Stanford Center for Biomedical Informatics Research
An Ontology-Based Approach for Computational Phenomics: Application to Autism Spectrum Disorder Stanford Center for Biomedical Informatics Research Psychiatric Genetics Phenotyping Terminology Ontology
More informationDefined versus Asserted Classes: Working with the OWL Ontologies. NIF Webinar February 9 th 2010
Defined versus Asserted Classes: Working with the OWL Ontologies NIF Webinar February 9 th 2010 Outline NIFSTD ontologies in brief Multiple vs Single hierarchy of classes/ Asserted vs Inferred classes/primitive
More informationNIH Public Access Author Manuscript Stud Health Technol Inform. Author manuscript; available in PMC 2010 February 28.
NIH Public Access Author Manuscript Published in final edited form as: Stud Health Technol Inform. 2009 ; 150: 537 541. An Evolutionary Approach to the Representation of Adverse Events Werner Ceusters
More informationBuilding a Diseases Symptoms Ontology for Medical Diagnosis: An Integrative Approach
Building a Diseases Symptoms Ontology for Medical Diagnosis: An Integrative Approach Osama Mohammed, Rachid Benlamri and Simon Fong* Department of Software Engineering, Lakehead University, Ontario, Canada
More informationAN ONTOLOGICAL APPROACH TO REPRESENTING AND REASONING WITH TEMPORAL CONSTRAINTS IN CLINICAL TRIAL PROTOCOLS
AN ONTOLOGICAL APPROACH TO REPRESENTING AND REASONING WITH TEMPORAL CONSTRAINTS IN CLINICAL TRIAL PROTOCOLS Ravi D. Shankar, Susana B. Martins, Martin J. O Connor and Amar K. Das Stanford Medical Informatics,
More informationOntologies for the Study of Neurological Disease
Alexander P. Cox 1, Mark Jensen 1, William Duncan 1, Bianca Weinstock-Guttman 3, Kinga Szigiti 3, Alan Ruttenberg 2, Barry Smith 1 and Alexander D. Diehl 3* 1 Department of Philosophy, University at Buffalo,
More informationAn Evolutionary Approach to the Representation of Adverse Events
Medical Informatics in a United and Healthy Europe K.-P. Adlassnig et al. (Eds.) IOS Press, 2009 2009 European Federation for Medical Informatics. All rights reserved. doi:10.3233/978-1-60750-044-5-537
More informationSemantic Alignment between ICD-11 and SNOMED-CT. By Marcie Wright RHIA, CHDA, CCS
Semantic Alignment between ICD-11 and SNOMED-CT By Marcie Wright RHIA, CHDA, CCS World Health Organization (WHO) owns and publishes the International Classification of Diseases (ICD) WHO was entrusted
More informationResearch Scholar, Department of Computer Science and Engineering Man onmaniam Sundaranar University, Thirunelveli, Tamilnadu, India.
DEVELOPMENT AND VALIDATION OF ONTOLOGY BASED KNOWLEDGE REPRESENTATION FOR BRAIN TUMOUR DIAGNOSIS AND TREATMENT 1 1 S. Senthilkumar, 2 G. Tholkapia Arasu 1 Research Scholar, Department of Computer Science
More informationCase-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials
Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials Riccardo Miotto and Chunhua Weng Department of Biomedical Informatics Columbia University,
More informationThe Nuts and Bolts of Diagnosing Autism Spectrum Disorders In Young Children. Overview
The Nuts and Bolts of Diagnosing Autism Spectrum Disorders In Young Children Jessica Greenson, Ph.D. Autism Center University of Washington Overview Diagnostic Criteria Current: Diagnostic & Statistical
More informationFoundations of AI. 10. Knowledge Representation: Modeling with Logic. Concepts, Actions, Time, & All the Rest
Foundations of AI 10. Knowledge Representation: Modeling with Logic Concepts, Actions, Time, & All the Rest Wolfram Burgard, Andreas Karwath, Bernhard Nebel, and Martin Riedmiller 10/1 Contents Knowledge
More informationDeconstructing the DSM-5 By Jason H. King
Deconstructing the DSM-5 By Jason H. King Assessment and diagnosis of autism spectrum disorder For this month s topic, I am excited to share my recent experience using the fifth edition of the Diagnostic
More informationAdvancing methods to develop behaviour change interventions: A Scoping Review of relevant ontologies
Advancing methods to develop behaviour change interventions: A Scoping Review of relevant ontologies Participating organisations Emma Norris @EJ_Norris Ailbhe Finnerty Janna Hastings Gillian Stokes Susan
More informationCausal Knowledge Modeling for Traditional Chinese Medicine using OWL 2
Causal Knowledge Modeling for Traditional Chinese Medicine using OWL 2 Peiqin Gu College of Computer Science, Zhejiang University, P.R.China gupeiqin@zju.edu.cn Abstract. Unlike Western Medicine, those
More informationWhat is Autism? -Those with the most severe disability need a lot of help with their daily lives whereas those that are least affected may not.
Autism Summary Autism What is Autism? The Autism Spectrum Disorder (ASD) is a developmental disability that can have significant implications on a child's ability to function and interface with the world
More informationOpportunities for Statistical Modeling and Computation at the National Institute of Mental Health (NIMH), NIH
Presenter: Abera Wouhib, Ph.D. Mathematical Statistician with Opportunities for Statistical Modeling and Computation at the National Institute of Mental Health (NIMH), NIH Greg Farber, Ph.D. Director,
More informationAPPLYING ONTOLOGY AND SEMANTIC WEB TECHNOLOGIES TO CLINICAL AND TRANSLATIONAL STUDIES
APPLYING ONTOLOGY AND SEMANTIC WEB TECHNOLOGIES TO CLINICAL AND TRANSLATIONAL STUDIES Cui Tao, PhD Assistant Professor of Biomedical Informatics University of Texas Health Science Center at Houston School
More informationThe NIMH Data Repositories
The NIMH Data Repositories November 5, 2014 Greg Farber, Ph.D. Director Office of Technology Development and Coordination National Institute of Mental Health National Institutes of Health 1 Expansion to
More informationFactors Influencing How Parents Report. Autism Symptoms on the ADI-R
Factors Influencing How Parents Report Autism Symptoms on the ADI-R Diana Wexler Briarcliff High School Diana Wexler Briarcliff High School 1 Abstract Background: The Autism Diagnostic Interview - Revised
More information5. Diagnostic Criteria
5. Diagnostic Criteria The questions that are going to be answered in this chapter are: What are the diagnostic criteria of ASD? Are the diagnostic criteria laid down in the DSM-IV-TR or ICD-10 manuals
More information38 Int'l Conf. Bioinformatics and Computational Biology BIOCOMP'16
38 Int'l Conf. Bioinformatics and Computational Biology BIOCOMP'16 PGAR: ASD Candidate Gene Prioritization System Using Expression Patterns Steven Cogill and Liangjiang Wang Department of Genetics and
More informationRepresentation of Part-Whole Relationships in SNOMED CT
Representation of Part-Whole Relationships in SNOMED CT A. Patrice Seyed 1, Alan Rector 2, Uli Sattler 2, Bijan Parsia 2, and Robert Stevens 2 1 Department of Computer Science and Engineering, University
More informationDiagnosis Advancements. Licensee OAPL (UK) Creative Commons Attribution License (CC-BY) Research study
Page 1 of 6 Diagnosis Advancements Relationship between Stereotyped Behaviors and Restricted Interests (SBRIs) measured on the Autism Diagnostic Observation Schedule (ADOS) and diagnostic results. C Schutte
More informationBrief introduction to NeuroLex. Stephen D. Larson NeuroML 3 rd Annual Workshop London - 3/31/11
Brief introduction to NeuroLex Stephen D. Larson NeuroML 3 rd Annual Workshop London - 3/31/11 Overview Brief introduction to linked data Value of ontologies for neuroscience Neuroscience information framework:
More informationHeiner Oberkampf. DISSERTATION for the degree of Doctor of Natural Sciences (Dr. rer. nat.)
INTEGRATED REPRESENTATION OF CLINICAL DATA AND MEDICAL KNOWLEDGE AN ONTOLOGY-BASED APPROACH FOR THE RADIOLOGY DOMAIN Heiner Oberkampf DISSERTATION for the degree of Doctor of Natural Sciences (Dr. rer.
More informationEvaluating the Behavioral and Developmental Interventions for Autism Spectrum Disorder
International Journal of Information Sciences and Application. ISSN 0974-2255 Volume 6, Number 1 (2014), pp. 1-10 International Research Publication House http://www.irphouse.com Evaluating the Behavioral
More informationORC: an Ontology Reasoning Component for Diabetes
ORC: an Ontology Reasoning Component for Diabetes Özgür Kafalı 1, Michal Sindlar 2, Tom van der Weide 2 and Kostas Stathis 1 1 Department of Computer Science Royal Holloway, University of London, UK {ozgur.kafali,kostas.stathis}@rhul.ac.uk
More informationASHA Comments* (ASHA Recommendations Compared to DSM-5 Criteria) Austism Spectrum Disorder (ASD)
DSM-5 (Criteria and Major Changes for SLP-Related Conditions) Individuals meeting the criteria will be given a diagnosis of autism spectrum disorder with three levels of severity based on degree of support
More informationUnderstanding Autism. Julie Smith, MA, BCBA. November 12, 2015
Understanding Autism Julie Smith, MA, BCBA November 12, 2015 2 Overview What is Autism New DSM-5; changes to diagnosis Potential causes Communication strategies Managing difficult behaviors Effective programming
More informationA Lexical-Ontological Resource forconsumerheathcare
A Lexical-Ontological Resource forconsumerheathcare Elena Cardillo FBK-IRST, Via Sommarive 18, 38123 Trento, Italy cardillo@fbk.eu Abstract. In Consumer Healthcare Informatics it is still difficult for
More informationAUTISM SPECTRUM DISORDER: DSM-5 DIAGNOSTIC CRITERIA. Lisa Joseph, Ph.D.
AUTISM SPECTRUM DISORDER: DSM-5 DIAGNOSTIC CRITERIA Lisa Joseph, Ph.D. Autism Spectrum Disorder Neurodevelopmental disorder Reflects understanding of the etiology of disorder as related to alterations
More informationHow to code rare diseases with international terminologies?
How to code rare diseases with international terminologies? Ana Rath Inserm US14, Paris, France ana.rath@inserm.fr Special thanks to Prof Paul Landais for his kind presentation. Needs for terminologies
More informationStepwise Knowledge Acquisition in a Fuzzy Knowledge Representation Framework
Stepwise Knowledge Acquisition in a Fuzzy Knowledge Representation Framework Thomas E. Rothenfluh 1, Karl Bögl 2, and Klaus-Peter Adlassnig 2 1 Department of Psychology University of Zurich, Zürichbergstraße
More informationA Content Model for the ICD-11 Revision
A Content Model for the ICD-11 Revision Samson W. Tu 1, Olivier Bodenreider 2, Can Çelik 3, Christopher G. Chute 4, Sam Heard 5, Robert Jakob 3, Guoquian Jiang 4, Sukil Kim 6, Eric Miller 7, Mark M. Musen
More informationExploiting deduction and abduction services for information retrieval. Ralf Moeller Hamburg University of Technology
Exploiting deduction and abduction services for information retrieval Ralf Moeller Hamburg University of Technology Seman&c Technologies: Data Descrip&ons Ontologies (specified in, e.g., OWL, UML) (aka
More informationInternational Journal of Software and Web Sciences (IJSWS)
International Association of Scientific Innovation and Research (IASIR) (An Association Unifying the Sciences, Engineering, and Applied Research) ISSN (Print): 2279-0063 ISSN (Online): 2279-0071 International
More informationBinding Ontologies and Coding Systems to Electronic Health Records and Message
Binding Ontologies and Coding Systems to Electronic Health Records and Message Alan Rector 1, Rahil Qamar 1 & Tom Marley 2 1 University of Manchester 2 University of Salford with acknowledgements to the
More informationStandardize and Optimize. Trials and Drug Development
Informatics Infrastructure to Standardize and Optimize Quantitative Imaging in Clinical Trials and Drug Development Daniel L. Rubin, MD, MS Assistant Professor of Radiology Member, Stanford Cancer Center
More informationAn introduction to case finding and outcomes
An introduction to case finding and outcomes Dr Harshana Liyanage Department of Clinical & Experimental Medicine University of Surrey Wednesday, 25 January 2017 1 Objectives Problems with routine data
More informationRole Representation Model Using OWL and SWRL
Role Representation Model Using OWL and SWRL Kouji Kozaki, Eiichi Sunagawa, Yoshinobu Kitamura, Riichiro Mizoguchi The Institute of Scientific and Industrial Research (ISIR), Osaka University 8-1 Mihogaoka,
More informationAPPROVAL SHEET. Uncertainty in Semantic Web. Doctor of Philosophy, 2005
APPROVAL SHEET Title of Dissertation: BayesOWL: A Probabilistic Framework for Uncertainty in Semantic Web Name of Candidate: Zhongli Ding Doctor of Philosophy, 2005 Dissertation and Abstract Approved:
More informationSemantic Science: machine understandable scientific theories and data
Semantic Science: machine understandable scientific theories and data David Poole http://www.cs.ubc.ca/spider/poole/ October 13, 2007 Abstract The aim of semantic science is to have scientific data and
More informationEvaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms
Evaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms Václav Papež 1,2,*, MSc, Spiros Denaxas 1,2,*, PhD, Harry Hemingway 1,2, FRCP
More information! Introduction:! ! Prosodic abilities!! Prosody and Autism! !! Developmental profile of prosodic abilities for Portuguese speakers!
Marisa Filipe Dezembro de 2013 pdpsi10020@fpce.up.pt EXCL/MHC-LIN/0688/2012 Summary Introduction: Prosodic Abilities in Children and Young Adults with Typical & Non-Typical Development Prosodic abilities
More information10/18/2016. Vineland Adaptive Behavior Scales, Third Edition 1. Meet Dr. Saulnier. Bio. Celine A. Saulnier, PhD Vineland-3 Author
Vineland Adaptive Behavior Scales, Third Edition Celine A. Saulnier, PhD Vineland-3 Author Director of Research Operations at the Marcus Autism Center & Associate Professor in the Department of Pediatrics
More informationBackground on the issue Previous study with adolescents and adults: Current NIH R03 study examining ADI-R for Spanish speaking Latinos
Sandy Magaña Background on the issue Previous study with adolescents and adults: brief description of study examining comparison between whites and Latinos in on the ADI-R Current NIH R03 study examining
More informationORC: an Ontology Reasoning Component for Diabetes
ORC: an Ontology Reasoning Component for Diabetes Özgür Kafalı 1, Michal Sindlar 2, Tom van der Weide 2 and Kostas Stathis 1 1 Department of Computer Science Royal Holloway, University of London, Egham,
More informationMedical Necessity Guidelines: Applied Behavioral Analysis (ABA) including Early Intervention for RITogether
Medical Necessity Guidelines: Applied Behavioral Analysis (ABA) including Effective: August 1, 2017 Clinical Documentation and Prior Authorization Required Applies to: Coverage Guideline, No prior Authorization
More informationA Simple Pipeline Application for Identifying and Negating SNOMED CT in Free Text
A Simple Pipeline Application for Identifying and Negating SNOMED CT in Free Text Anthony Nguyen 1, Michael Lawley 1, David Hansen 1, Shoni Colquist 2 1 The Australian e-health Research Centre, CSIRO ICT
More informationSAGE. Nick Beard Vice President, IDX Systems Corp.
SAGE Nick Beard Vice President, IDX Systems Corp. Sharable Active Guideline Environment An R&D consortium to develop the technology infrastructure to enable computable clinical guidelines, that will be
More informationA Comparison of Collaborative Filtering Methods for Medication Reconciliation
A Comparison of Collaborative Filtering Methods for Medication Reconciliation Huanian Zheng, Rema Padman, Daniel B. Neill The H. John Heinz III College, Carnegie Mellon University, Pittsburgh, PA, 15213,
More informationINFORMATION PAPER: INTRODUCING THE NEW DSM-5 DIAGNOSTIC CRITERIA FOR AUTISM SPECTRUM DISORDER
INFORMATION PAPER: INTRODUCING THE NEW DSM-5 DIAGNOSTIC CRITERIA FOR AUTISM SPECTRUM DISORDER What is the DSM-5? The Diagnostic and Statistical Manual of Mental Disorders (the DSM) is developed by the
More informationAutomatic generation of MedDRA terms groupings using an ontology
Automatic generation of MedDRA terms groupings using an ontology Gunnar DECLERCK a,1, Cédric BOUSQUET a,b and Marie-Christine JAULENT a a INSERM, UMRS 872 EQ20, Université Paris Descartes, France. b Department
More informationTowards Best Practices for Crowdsourcing Ontology Alignment Benchmarks
Towards Best Practices for Crowdsourcing Ontology Alignment Benchmarks Reihaneh Amini, Michelle Cheatham, Pawel Grzebala, and Helena B. McCurdy Data Semantics Laboratory, Wright State University, Dayton,
More informationWeighted Ontology and Weighted Tree Similarity Algorithm for Diagnosing Diabetes Mellitus
2013 International Conference on Computer, Control, Informatics and Its Applications Weighted Ontology and Weighted Tree Similarity Algorithm for Diagnosing Diabetes Mellitus Widhy Hayuhardhika Nugraha
More informationTeaching Students with Special Needs in Inclusive Settings: Exceptional Learners Chapter 9: Autism Spectrum Disorders
Teaching Students with Special Needs in Inclusive Settings: Exceptional Learners Chapter 9: Autism Spectrum Disorders Background Autistic is a broad term coined in the twentieth century by Bleuler that
More informationAn Ontology for Healthcare Quality Indicators: Challenges for Semantic Interoperability
414 Digital Healthcare Empowering Europeans R. Cornet et al. (Eds.) 2015 European Federation for Medical Informatics (EFMI). This article is published online with Open Access by IOS Press and distributed
More informationPROPOSED WORK PROGRAMME FOR THE CLEARING-HOUSE MECHANISM IN SUPPORT OF THE STRATEGIC PLAN FOR BIODIVERSITY Note by the Executive Secretary
CBD Distr. GENERAL UNEP/CBD/COP/11/31 30 July 2012 ORIGINAL: ENGLISH CONFERENCE OF THE PARTIES TO THE CONVENTION ON BIOLOGICAL DIVERSITY Eleventh meeting Hyderabad, India, 8 19 October 2012 Item 3.2 of
More informationExpert System Profile
Expert System Profile GENERAL Domain: Medical Main General Function: Diagnosis System Name: INTERNIST-I/ CADUCEUS (or INTERNIST-II) Dates: 1970 s 1980 s Researchers: Ph.D. Harry Pople, M.D. Jack D. Myers
More informationA Framework for Conceptualizing, Representing, and Analyzing Distributed Interaction. Dan Suthers
1 A Framework for Conceptualizing, Representing, and Analyzing Distributed Interaction Dan Suthers Work undertaken with Nathan Dwyer, Richard Medina and Ravi Vatrapu Funded in part by the U.S. National
More informationQuestions for Eric London: Alternative diagnoses for autism
OPINION, Q&A Questions for Eric London: Alternative diagnoses for autism BY JESSICA WRIGHT 2 JANUARY 2015 1 / 7 Deep dive: Listing detailed symptoms rather than assigning a single diagnostic label may
More information1/30/2018. Adaptive Behavior Profiles in Autism Spectrum Disorders. Disclosures. Learning Objectives
Adaptive Behavior Profiles in Autism Spectrum Disorders Celine A. Saulnier, PhD Associate Professor Emory University School of Medicine Vineland Adaptive Behavior Scales, Third Edition 1 Disclosures As
More informationTable 1: Comparison of DSM-5 and DSM-IV-TR Diagnostic Criteria. Autism Spectrum Disorder (ASD) Pervasive Developmental Disorders Key Differences
Comparison of the Diagnostic Criteria for Autism Spectrum Disorder Across DSM-5, 1 DSM-IV-TR, 2 and the Individuals with Disabilities Act (IDEA) 3 Definition of Autism Colleen M. Harker, M.S. & Wendy L.
More informationBrooke DePoorter M.Cl.Sc. (SLP) Candidate University of Western Ontario: School of Communication Sciences and Disorders
Critical Review: In school-aged children with Autism Spectrum Disorder (ASD), what oral narrative elements differ from their typically developing peers? Brooke DePoorter M.Cl.Sc. (SLP) Candidate University
More informationDSM-IV Criteria. (1) qualitative impairment in social interaction, as manifested by at least two of the following:
DSM-IV Criteria Autistic Disorder A. A total of six (or more) items from (1), (2), and (3), with at least two from (1), and one each from (2) and (3): (1) qualitative impairment in social interaction,
More informationCover Page. The handle holds various files of this Leiden University dissertation.
Cover Page The handle http://hdl.handle.net/1887/19149 holds various files of this Leiden University dissertation. Author: Maljaars, Janne Pieternella Wilhelmina Title: Communication problems in children
More informationMeasurement Invariance (MI): a general overview
Measurement Invariance (MI): a general overview Eric Duku Offord Centre for Child Studies 21 January 2015 Plan Background What is Measurement Invariance Methodology to test MI Challenges with post-hoc
More informationAutism. Laura Schreibman HDP1 11/29/07 MAIN DIAGNOSTIC FEATURES OF AUTISTIC DISORDER. Deficits in social attachment and behavior
Autism Laura Schreibman HDP1 11/29/07 MAIN DIAGNOSTIC FEATURES OF AUTISTIC DISORDER Deficits in social attachment and behavior Deficits in verbal and nonverbal communication Presence of perseverative,
More informationAnalyzing the Semantics of Patient Data to Rank Records of Literature Retrieval
Proceedings of the Workshop on Natural Language Processing in the Biomedical Domain, Philadelphia, July 2002, pp. 69-76. Association for Computational Linguistics. Analyzing the Semantics of Patient Data
More informationInvestigating implementing CEN with HL7 V3 and SNOMED CT Final Report
Investigating implementing CEN 13606 with HL7 V3 and SNOMED CT Programme NPFIT Document Record ID Key Sub-Prog / Project Technology Office Prog. Director P. Jones Status
More informationTime-Oriented Question Answering from Clinical Narratives Using Semantic-Web Techniques
Time-Oriented Question Answering from Clinical Narratives Using Semantic-Web Techniques Cui Tao, Haorld R. Solbrig, Deepak K. Sharma, Wei-Qi Wei, Guergana K. Savova, and Christopher G. Chute Division of
More informationNew Mexico TEAM Professional Development Module: Autism
[Slide 1]: Welcome Welcome to the New Mexico TEAM technical assistance module on making eligibility determinations under the category of autism. This module will review the guidance of the NM TEAM section
More informationCombining Archetypes with Fast Health Interoperability Resources in Future-proof Health Information Systems
180 Digital Healthcare Empowering Europeans R. Cornet et al. (Eds.) 2015 European Federation for Medical Informatics (EFMI). This article is published online with Open Access by IOS Press and distributed
More informationUsing the CEN/ISO Standard for Categorial Structure to Harmonise the Development of WHO International Terminologies
Medical Informatics in a United and Healthy Europe K.-P. Adlassnig et al. (Eds.) IOS Press, 2009 2009 European Federation for Medical Informatics. All rights reserved. doi:10.3233/978-1-60750-044-5-255
More informationStudy Endpoint Considerations: Final PRO Guidance and Beyond
Study Endpoint Considerations: Final PRO Guidance and Beyond Laurie Burke Associate Director for Study Endpoints and Labeling OND/CDER/FDA Presented at: FIRST ANNUAL PATIENT REPORTED OUTCOMES (PRO) CONSORTIUM
More informationOccupational Health in the 11 th Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD11)
Occupational Health in the 11 th Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD11) Dr Ivan D. Ivanov Department of Public Health, Environmental and
More informationAutism Spectrum Disorders: An update on research and clinical practices for SLPs
DSM-IV to DSM-5: Primary Changes Autism Spectrum Disorders: An update on research and clinical practices for SLPs Laurie Swineford, PhD CCC-SLP Washington State University DSM-IV Previously we used the
More informationAdaptive Behavior Profiles in Autism Spectrum Disorders
Adaptive Behavior Profiles in Autism Spectrum Disorders Celine A. Saulnier, PhD Associate Professor Emory University School of Medicine Director of Research Operations Marcus Autism Center Vineland Adaptive
More informationAutism/Pervasive Developmental Disorders Update. Kimberly Macferran, MD Pediatric Subspecialty for the Primary Care Provider December 2, 2011
Autism/Pervasive Developmental Disorders Update Kimberly Macferran, MD Pediatric Subspecialty for the Primary Care Provider December 2, 2011 Overview Diagnostic criteria for autism spectrum disorders Screening/referral
More informationWhat s in a name? Autism is a Syndrome. Autism Spectrum Disorders 6/30/2011. Autism Spectrum Disorder (ASD) vs Pervasive Developmental Disorder (PDD)
Autism is a Syndrome A group of symptoms that tend to cluster together Share a common natural history Not necessarily a single etiology What s in a name? Autism Spectrum Disorder (ASD) vs Pervasive Developmental
More informationPragmatic language in fragile X syndrome, autism, and Down syndrome
Pragmatic language in fragile X syndrome, autism, and Down syndrome Jessica Klusek, MS CCC-SLP FPG Child Development Institute (FPG) University of North Carolina at Chapel Hill (UNC) Molly Losh, PhD Northwestern
More informationPragmatic language impairments
Pragmatic language impairments Dorothy Bishop Wellcome Principal Research Fellow Department of Experimental Psychology University of Oxford 1 Oral communication involves: COMPREHENSION decoding speech
More informationDiagnostic Evaluation
The Els Center of Excellence 18370 Limestone Creek Road Jupiter, FL 33458 561-320-9520 Diagnostic Evaluation Christine Honsberger, Ed.D., BCBA & Jessica Weber, Ph.D., BCBA-D Elsforautism.org DSM-V Autism
More informationFact Sheet 8. DSM-5 and Autism Spectrum Disorder
Fact Sheet 8 DSM-5 and Autism Spectrum Disorder A diagnosis of autism is made on the basis of observed behaviour. There are no blood tests, no single defining symptom and no physical characteristics that
More informationHealth informatics Digital imaging and communication in medicine (DICOM) including workflow and data management
INTERNATIONAL STANDARD ISO 12052 Second edition 2017-08 Health informatics Digital imaging and communication in medicine (DICOM) including workflow and data management Informatique de santé Imagerie numérique
More informationLow Functioning Autism Spectrum Disorder
Low Functioning Autism Spectrum Disorder Walter E. Kaufmann Center for Translational Research Greenwood Genetic Center Department of Neurology, Boston Children s Hospital MIT Simons Center for the Social
More informationA Descriptive Delta for Identifying Changes in SNOMED CT
A Descriptive Delta for Identifying Changes in SNOMED CT Christopher Ochs, Yehoshua Perl, Gai Elhanan Department of Computer Science New Jersey Institute of Technology Newark, NJ, USA {cro3, perl, elhanan}@njit.edu
More informationEducation Options for Children with Autism
Empowering children with Autism and their families through knowledge and support Education Options for Children with Autism Starting school is a major milestone in a child s life, and a big step for all
More informationKaiser Permanente Convergent Medical Terminology (CMT)
Kaiser Permanente Convergent Medical Terminology (CMT) Using Oxford RDFox and SNOMED for Quality Measures Peter Hendler, MD Alan Abilla, RN, MS About Kaiser Permanente Largest health maintenance organization
More informationDeriving an Abstraction Network to Support Quality Assurance in OCRe
Deriving an Abstraction Network to Support Quality Assurance in OCRe Christopher Ochs, MS 1, Ankur Agrawal, BE 1, Yehoshua Perl, PhD 1, Michael Halper, PhD 1, Samson W. Tu, MS 3, Simona Carini, MA 2, Ida
More informationThe Clinical Progress of Autism Spectrum Disorders in China. Xi an children s hospital Yanni Chen MD.PhD
The Clinical Progress of Autism Spectrum Disorders in China Xi an children s hospital Yanni Chen MD.PhD Conception The autism spectrum disorders (ASDs) are neurodevelopmental disability characterized by
More informationDevelopment of Action Server and Client for Pick and Place with PR2 Robot
Development of Action Server and Client for Pick and Place with PR2 Robot Callie Clement Tulane University: Class of 2015 School of Science and Engineering: Biomedical Engineering New Orleans, LA cclemen1@tulane.edu
More informationThe Date-Time Vocabulary, and Mapping SBVR to OWL
November 8, 2012 The Date-Time Vocabulary, and Mapping SBVR to OWL Mark H. Linehan IBM Research mlinehan@us.ibm.com Agenda The Date-Time Vocabulary What is the Date-Time Vocabulary? Previous Work What
More informationOn the Contributors to System Smartness : A Med Net Agent System Case Study
On the Contributors to System Smartness : A Med Net Agent System Case Study M. Lyell, W. Krueger, W. Chen Intelligent Automation, Inc. 15400 Calhoun Drive, Suite 400 Rockville MD 20855 USA {mlyell, wkrueger,
More informationReinforcement Learning in RAT, Approaches
Machine Learning in Robot Assisted Therapy (RAT) Applications of Supervised, Unsupervised and Reinforcement Learning in RAT, Approaches Alexander Kohles Lennart Aigner SS 2018 Main Question How to improve
More informationLanguage Comprehension Predicts Later Cognitive Ability and Symptom Severity in Toddlers with ASD
Language Comprehension Predicts Later Cognitive Ability and Symptom Severity in Toddlers with ASD McGarry, E., Fiorello, K., Heldenberg, S., Reifler, A., Klaiman, C., Saulnier, C., & Lewis, M.. Marcus
More informationAutism Spectrum Disorder What is it?
Autism Spectrum Disorder What is it? Robin K. Blitz, MD Resident Autism Diagnostic Clinic Lecture Series #1 Learning Objectives What can we talk about in 20 minutes? What is Autism? What are the Autism
More informationThis is a pre-publication version of the article published in the Journal of Clinical Practice in Speech Language Pathology
CHANGING THE WAY WE DIAGNOSE AUTISM 1 This is a pre-publication version of the article published in the Journal of Clinical Practice in Speech Language Pathology Changing the way we diagnose autism: Implications
More informationA Web Tool for Building Parallel Corpora of Spoken and Sign Languages
A Web Tool for Building Parallel Corpora of Spoken and Sign Languages ALEX MALMANN BECKER FÁBIO NATANAEL KEPLER SARA CANDEIAS July 19,2016 Authors Software Engineer Master's degree by UFSCar CEO at Porthal
More information