Improving healthcare with AI
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The document provides a historical overview of artificial intelligence (AI) and its evolution, highlighting key figures and milestones in the field, such as John McCarthy and Marvin Minsky. It emphasizes the transition from traditional AI to machine learning and deep learning, showcasing various healthcare applications, including disease detection and automation of document processing. The document argues for the transformative potential of AI in healthcare, enabling earlier detection and more accurate diagnoses.
Improving healthcare with AI
- 1. ©2018, Amazon Web Services, Inc. or its affiliates. All rights reserved Improving healthcare with AI Julien Simon PrincipalTechnical Evangelist, AI & Machine Learning, AWS
- 2. A quick history of Artificial Intelligence
- 3. John McCarthy (1927-2011) 1956 - Coined the term “Artificial Intelligence” 1958 - Invented LISP 1971 - Received the Turing Award Forbidden Planet 1956 Dartmouth Summer Research Project Robbie the Robot
- 4. Artificial Intelligence: design software applications which exhibit human-like behavior, e.g. speech, natural language processing, reasoning or intuition
- 5. Gazing into the crystal ball • 1958 Herbert Simon and Allen Newell “Within 10 years a digital computer will be the world's chess champion” • 1965 Herbert Simon “Machines will be capable, within 20 years, of doing any work a man can do” • 1967 Marvin Minsky “Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved.” • 1970 Marvin Minsky “In from 3 to 8 years we will have a machine with the general intelligence of an average human being” https://en.wikipedia.org/wiki/History_of_artificial_intelligence Herbert Simon (1916-2001) 1975 - Received the Turing Award 1978 - Received the Nobel Prize in Economics Allen Newell (1927-1992) 1975 - Received the Turing Award
- 6. It’s 2001.Where is HAL? Marvin Minsky (1927-2016) 1959 - Co-founded the MIT AI Lab 1968 - Advised Kubrick on “2001: A Space Odyssey” 1969 - Received the Turing Award HAL 9000 (1992-2001) « No program today can distinguish a dog from a cat, or recognize objects in typical rooms, or answer questions that 4-year-olds can! »
- 7. Artificial Intelligence: design software applications which exhibit human-like behavior, e.g. speech, natural language processing, reasoning or intuition Machine Learning: teach machines to learn without being explicitly programmed
- 8. Millions of users… Mountains of data… Commodity hardware… Bright engineers… Need to make money! Gasoline waiting for a match! 12/2004 - Google publishes seminal paper on processing data at scale 04/2006 –Yahoo implements it The rest is history
- 9. Fast forward a few years • Machine Learning is now a commodity, but still no HAL in sight • Machine Learning doesn’t work well on unstructured data (images, video, speech, freeform text, etc.) • These tasks that are easy for people but hard to describe formally • Is there a way to get informal knowledge into a computer? • Enter neural networks and Deep Learning
- 10. Artificial Intelligence: design software applications which exhibit human-like behavior, e.g. speech, natural language processing, reasoning or intuition Machine Learning: teach machines to learn without being explicitly programmed Deep Learning: using neural networks, teach machines to learn from complex data where features cannot be explicitly expressed
- 11. Healthcare Applications of Deep Learning
- 12. Finding a doctor near you https://www.zocdoc.com https://aws.amazon.com/blogs/machine-learning/zocdoc-builds-patient-confidence-using-tensorflow-on-aws/ • Zocdoc is an online healthcare scheduling service, locating a doctor in your area and optimizing costs • With Zocdoc’s Insurance Checker, a patient just has to take a photo of their health insurance card.The system uses Deep Learning-based computer vision to scan the ID card and extract the correct policy ID information.
- 14. Detecting fractures https://www.azmed.co Non-displaced scaphoid fracture Automatic reporting
- 15. Auto-contouring in seconds https://www.arterys.com https://aws.amazon.com/solutions/case-studies/arterys/ Arterys can contour cardiac anatomy as accurately as experts, but takes only 15-20 seconds instead of the 45-60 minutes required to do it manually
- 16. Early detection of Alzheimer’s disease https://medicalxpress.com/news/2018-11-artificial-intelligence-alzheimer-years-diagnosis.html The algorithm achieved 100 percent sensitivity at detecting the disease an average of more than six years prior to the final diagnosis.
- 17. « AI will never replace doctors » (blah blah blah) 5.8 billion people around the world can’t access an expert physician
- 18. Detecting cervical cancer with a smartphone https://www.mobileodt.com/ http://www.itnewsafrica.com/2017/11/interview-mobileodt-using-aws-cloud-to-save-lives/ 270,000 women die every year of cervical cancer
- 19. What about people who need constant supervision? In 2014, 1 in 59 U.S. children had autism In 2017, 44 million people worldwide have Alzheimer’s disease
- 20. Pollexy: building a special needs voice assistant https://aws.amazon.com/blogs/aws/pollexy-building-a-special-needs-voice-assistant-with-amazon-polly-and-raspberry-pi/ https://www.youtube.com/watch?v=BUewiOZTNzM
- 21. AI is a revolution for healthcare professionals Earlier detection Faster, more accurate diagnosis Personalized, optimal treatment Saving time, paperwork and exams Letting them focus on the most important thing…
- 22. HUMANS
- 23. Resources General Case studies https://aws.amazon.com/health/case-studies/ Getting in touch https://aws.amazon.com/contact-us/ Technical Getting started https://aws.amazon.com/getting-started/ Machine Learning https://ml.aws/
- 24. Julien Simon PrincipalTechnical Evangelist, AI & Machine Learning, AWS Twitter: @julsimon Medium: https://medium.com/@julsimon
Editor's Notes
- #21: https://aws.amazon.com/blogs/aws/pollexy-building-a-special-needs-voice-assistant-with-amazon-polly-and-raspberry-pi/ https://www.youtube.com/watch?v=BUewiOZTNzM