Artificial Intelligence AI for Smarter Healthcare

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1 Artificial Intelligence AI for Smarter Healthcare

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3 What is Artificial Intelligence? What is Artificial Intelligence? Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

4 A.I. in Healthcare new startups in By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries. Harpreet Singh Buttar, analyst at Frost & Sullivan.

5 Healthcare A.I. Marketplace

6 Consumer Adoption of A.I. enabled healthcare Cardiac Monitoring or monitor my heart condition - 37% Heart rhythm and arrhythmia detection 35% Provide customized fitness and health based on history 34% Laboratory tests such as blood work 30% Source: PwC Survey 2016

7 Patient Adoption is critical to A.I. success Medical Errors Medical error is currently the third leading cause of death in the US, and as many as one in six patients in the British NHS receive incorrect diagnoses. A.I. can be the Solution! AI can potentially transform medical practice and drastically reduce the number of medical errors, as well as provide a host of other benefits. Medical Responsibility Usually when something goes wrong, it is a fairly straightforward matter to determine blame. A misdiagnosis, for instance, would likely be the responsibility of the presiding physician. A faulty machine or medical device that harms a patient would likely see the manufacturer or operator held to account. What would this mean for an AI?

8 Patient Adoption is critical to A.I. success Fears of AI in Healthcare The survey indicates that the top two fears patients and caregivers have when it comes to artificial intelligence are lack of human oversight and the potential for machine errors leading to mismanagement of their health. No Substitute for Your Doctor When it comes to the possibilities of doctors being replaced by algorithms or robots, fears are clearly evident with fewer than 20 percent of patients surveyed perceiving any benefit to their future healthcare in receiving diagnosis or treatment recommendations from a virtual assistant. Strong Comfort in Using AI to Scale and Support Nurses Switch the focus to the critical role played by nurses in supporting patients, and a different picture emerges. 64% would be comfortable with a Virtual Nurse and 72% responded that their Virtual Nurse needs to have a nice bedside manner

9 A.I. Use Cases - Cancer Research To speed advances in the fight against cancer, the Cancer Moonshot initiative unites the Department of Energy (DOE), the National Cancer Institute (NCI) and other agencies with researchers at Oak Ridge, Lawrence Livermore, Argonne, and Los Alamos National Laboratories. NVIDIA is collaborating with the labs to help accelerate their AI framework called CANDLE as a common discovery platform, with the goal of achieving 10X annual increases in productivity for cancer researchers. This exascale framework will make it possible for scientists and researchers to use deep learning as well as computational sciences to address the urgent challenges of fighting cancer. The new NVIDIA DGX SATURNV supercomputer will help in this regard.

10 Accelerating Drug Discoveries with AI New drugs typically take 12 to 14 years and $2.6 billion to bring to market. BenevolentAI is using GPU deep learning to bring new therapies to market quickly and more affordably. They ve automated the process of identifying patterns within large amounts of research data, enabling scientists to form hypotheses and draw conclusions quicker than any human researcher could. For example, using the NVIDIA DGX-1 AI supercomputer, two potential drug targets for Alzheimer s were identified in less than one month.

11 AI advances the fight against breast cancer Breast cancer is the second leading cause of cancer death for women worldwide. Genomic tests help doctors determine a cancer s aggressiveness so they can prescribe appropriate treatment. But testing is expensive, tissue-destructive, and takes 10 to 14 days. Case Western Reserve is using GPU deep learning to develop an automated assessment of cancer risk at 1/20 the cost of current genomic tests.

12 AI predicts and prevents disease GPU deep learning is giving doctors a life-saving edge by identifying high-risk patients before diseases are diagnosed. Icahn School of Medicine at Mount Sinai built an AI-powered tool, Deep Patient, based on NVIDIA GPUs and the CUDA programming model. Deep Patient can analyze a patient s medical history to predict nearly 80 diseases up to 1 year prior to onset.

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14 Open Discussion 2017 The HCI Group 14