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AI in Healthcare


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Overview of AI with applications in healthcare.

Published in: Technology
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AI in Healthcare

  1. 1. 1© Ivy Data Science Ivy Data Science AI with Applications in Healthcare
  2. 2. © Ivy Data Science 2 AI State of Play © Ivy Data Science
  3. 3. AI is inspired by Nature - Biological Neuron Ivy Data Science AI with Applications v0.10 Peter Morgan Dec 2016 3© Ivy Data Science
  4. 4. Biological Neurons – Cajal, circa 1900 Ivy Data Science AI with Applications v0.10 Peter Morgan Dec 2016 4© Ivy Data Science
  5. 5. Biological Neurons – Cortical Columns Ivy Data Science AI with Applications v0.10 Peter Morgan Dec 2016 5© Ivy Data Science
  6. 6. Artificial Neural Network Ivy Data Science AI with Applications v0.10 Peter Morgan Dec 2016 6© Ivy Data Science
  7. 7. Enterprise technology has evolved with each wave of the Industrial Revolution – today it is AI
  8. 8. 1st Steam Power 3rd Computing 2nd Mass Production 19th Century 17th Century 21st Century 4th Artificial Intelligence 20th Century
  9. 9. © Ivy Data Science The Intelligence Revolution 9
  10. 10. Deep Learning hardware and algorithms along with increasing amounts of data are the foundation for the “fourth industrial revolution”
  11. 11. Deep learning is a new computing model that spans training, inference, and the billions of intelligent devices that will take advantage of deep learning to perform intelligent tasks
  12. 12. Deep Learning in the cloud - accelerating enterprise AI today
  13. 13. Example 1 – Microsoft cloud: “We’ve worked with Microsoft to create a lightning-fast AI platform that is available from on-premises with our DGX-1 supercomputer to the Microsoft Azure cloud.” - Jen-Hsun Huang CEO at NVIDIA
  14. 14. “By working closely with NVIDIA and harnessing the power of GPU-accelerated systems, we’ve made Cognitive Toolkit and Microsoft Azure the fastest, most versatile AI platform.” - Harry Shum Executive VP of AI and Research at Microsoft
  15. 15. “With Microsoft’s global reach, every company around the world can now tap the power of AI to transform their business.” - Jen-Hsun Huang CEO at NVIDIA
  16. 16. Example 2 – IBM: IBM CEO Gini Rometty saw a two trillion dollar opportunity in machine learning for enterprise. This ignited their recent drive in advancing GPU-based cloud computing …
  17. 17. The solution runs on an IBM server built specifically for AI and utilizes NVLink to optimize AI into the enterprise … And developed PowerAI that accelerates machine learning training and AI tasks
  18. 18. “PowerAI democratizes Deep Learning and other advanced analytics technologies by giving enterprise data scientists and research scientists alike an easy to deploy platform to rapidly advance their journey on AI.” - Ken King General Manager for OpenPOWER
  19. 19. “Putting GPU’s into the IBM system will speed up performance for such emerging workloads as AI, deep learning, and data analytics.” -eWeek
  20. 20. -Karl Freund Moor Insights & Strategy “With these partnerships in place, NVIDIA has aligned itself with two of the largest suppliers of enterprise IT technology and services to accelerate the adoption of AI in the enterprise and help take AI into the mainstream of global businesses.” READ FORBES ARTICLE
  21. 21. GOOGLE Example 3 - Google Cloud: Deep Learning is available for Google Compute Engine and Google Cloud Machine Learning users to create new AI services and applications Tesla P100 delivers a 12x increase in neural network training performance compared with a previous generation offering.
  22. 22. Example 4 – AWS: Amazon has boosted their cloud-computing performance with new GPU- Accelerated AWS instances that are designed for large-scale machine learning, deep learning, molecular modeling, and computational finance workloads.
  23. 23. “These (P2) instances were designed to chew through tough large-scale machine learning, deep learning, computational fluid dynamics, seismic analysis, molecular modeling, genomics, and computational finance workloads.” - Jeff Barr Chief Evangelist at AWS
  24. 24. SAP Example 5 – SAP: Enterprise software giant SAP is now using DGX-1 supercomputers to build machine learning solutions for SAP’s 320,000 customers in 190 countries. The system is designed to help data scientists innovate & get to market faster with AI applications.
  25. 25. These partnerships with the world’s largest companies allow Deep Learning platforms to be available for every company in the cloud today
  26. 26. AI Hardware Developments © Ivy Data Science 2929© Ivy Data Science
  27. 27. Nvidia - GPU Exponentials © Ivy Data Science 30© Ivy Data Science 30
  28. 28. GPU Faster than Moore’s Law © Ivy Data Science 31© Ivy Data Science 31
  29. 29. Computer Vision Accuracy © Ivy Data Science 32© Ivy Data Science 32
  30. 30. © Ivy Data Science 33 Nvidia DGX-1
  31. 31. © Ivy Data Science 34 Nvidia Pascal P100
  32. 32. © Ivy Data Science 35 AMD Radeon Vega
  33. 33. Facebook Big Sur Server © Ivy Data Science 36
  34. 34. The GPU in the cloud movement has quickly accelerated AI into one of today’s biggest enterprise technologies Next up FPGA’s and ASICs – already happening
  35. 35. ASIC Development Companies: • Wave (DPU) • Graphcore (IPU) • KnuEdge • Google (TPU) • Intel/Nervana Overviews: c872a0448be8#.6cxtp1fux 38© Ivy Data Science
  36. 36. © Ivy Data Science 39 Google TPU
  37. 37. © Ivy Data Science 40 AlphaGo – TPU Cluster
  38. 38. © Ivy Data Science 41 Time to train AlexNet Hardware Comparison – CPU v GPU v DPU (Wave ASIC)
  39. 39. AI in Healthcare • Detection • Diagnosis • Prediction • Drug discovery • Personalized medicine • Medical Imaging • Genomics • Cancer research • Brain tumors • Dermatology • Mental health • Speech patterns • Diabetes • Radiology © Ivy Data Science
  40. 40. Watson Tackles Cancer • Watson was tested on 1,000 cancer diagnoses made by human experts. In 99% of them, Watson recommended the same treatment as the oncologists • In 30% of the cases, Watson also found a treatment option the human doctors missed • Some treatments were based on research papers that the doctors had not read — more than 160,000 cancer research papers are published a year • Other treatment options surfaced in new clinical trials the oncologists had not yet seen announced on the web. Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 43© Ivy Data Science
  41. 41. AI - Accelerating the Healthcare Transformation
  42. 42. Cancer is the Epidemic of our Time
  43. 43. Leading to the creation of one of the most important initiatives … On January 2016, the White House announced its aim to deliver a decade’s worth of advances in cancer prevention, diagnosis, and treatment, in five years, with this initiative.
  44. 44. This initiative includes the building of an AI framework named CANDLE (Cancer Distributed Learning Environment) being developed by multiple organizations. It will help us change the way we understand cancer.
  45. 45. “Big Data and Computing Power together provide the possibility of significant insight into how genomics, family medical history, lifestyles, genetic changes can trigger cancer and how the cancers can be treated.” - Joe Biden Previous Vice President of the United States
  46. 46. The bright future of AI in healthcare only continues to become brighter… Enlitic Imaging & Diagnostics Insilico Medicine Drug Discovery & Aging Research Pathway Genomics Imaging & Diagnostics
  47. 47. “A patient gets a lung CT screening. By immediately giving the clinician the most accurate information, the patient is less likely to have a missed diagnosis or an unneeded biopsy.” Enlitic applies state of the art deep learning technology to medicine - Jeremy Howard Founder and CEO of Enlitic
  48. 48. “At Insilico we are working on a system to discover drug candidates and looking for new approaches to treat individual patients with rare diseases.” - Alex Zharvoronkov CEO at Insilico Medicine Insilico Medicine applies Deep Learning algorithms to drug discovery
  49. 49. “We are in the process of initiating disease specific studies for early cancer detection in high risk patients, including a study in lung cancer, and will publish the data in the appropriate forums.” - Glenn Braunstein Chief Medical Officer at Pathway Genomics Pathway Genomics developed a blood test kit with IBM Watson to test early cancer detection
  51. 51. References • Deep Genomics is applying GPU-based deep learning to understand how genetic variations can lead to disease • Arterys uses GPU-powered deep learning to speed analysis of medical images • GE Healthcare MRI machines help to diagnose heart disease • Atomwise – using deep learning to develop new pharmaceuticals • Deep Learning for Healthcare • Deep Learning for Medical Image Analysis html?id=WVqfDAAAQBAJ&source=kp_cover • Deep Learning for Detection of Diabetic Eye Disease diabetic.html • Retinal Assessment retina-assessment-and-diagnostic-services/ © Ivy Data Science 5757© Ivy Data Science
  52. 52. References • MIT barzilay-0216 • • Startups • Radiology highest-paid-doctors-obsolete/ • Stem cell development © Ivy Data Science
  53. 53. AI in Fintech Five main areas: • Alerting • Reporting • Advising • Trading • Investment For Example: • Anomaly detection • Risk Management • Insurance • Algorithmic Trading • Portfolio management Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 59© Ivy Data Science
  54. 54. Fintech – Use Cases • Alerting - Anomaly (Fraud) Detection. Can detect and predict irregular activity • Reporting - systems that can instantaneously analyze data, reason about what that analysis means and then generate natural language reports that inform many audiences. Useful in compliance and regulation • Advising - system has a “conceptual awareness” of client goals and needs • E.g., Watson gives veterans financial advice related to their transition from military to civilian life • Deep Learning is being used in algorithmic, high frequency trading • Ideal for creating investment portfolios Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 60© Ivy Data Science
  55. 55. The team was able to: • Process ~11,000 payments per second • Cut false alarm rates by 50% • Free up resources to combat true fraud PayPal is improving cybersecurity with deep learning © Ivy Data Science
  56. 56. General Reading on AI • Barrat, James, Our Final Invention, St. Martin's Griffin, 2014 • Brynjolfsson, Erik and Andrew McAfee, The Second Machine Age, W.W. Norton & Co., 2014 • Domingos, Pedro, The Master Algorithm, Basic Books, 2015 • Ford, Martin, Rise of the Robots: Technology and the Threat of a Jobless Future, Basic Books, 2015 • Kaku, Michio, The Future of the Mind, Doubleday, 2014 • Kurzweil, Ray, The Singularity is Near, Penguin Books, 2006 • Kurzweil, Ray, How to Create a Mind, Penguin Books, 2013 • Nowak, Peter, Humans 3.0: The Upgrading of the Species, Lyons Press, 2015 © Ivy Data Science 62
  57. 57. Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 63© Ivy Data Science
  58. 58. Training with Job Placement • Led by Experts from Harvard, Columbia, UMass, UCL • Real time paid projects in the last four weeks of bootcamp • Practical hands-on training that will prepare you for a career as a Data Scientist, Machine Learning or Deep Learning Practitioner • We also offer online training Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 64© Ivy Data Science
  59. 59. Network of Clients Ivy Data Science AI - State of Play v0.10 Peter Morgan Dec 2016 65© Ivy Data Science
  60. 60. Any Questions? © Ivy Data Science 66© Ivy Data Science 66
  61. 61. | @ivydatascience