Deep Medicine- How Artificial Intelligence Can Make Healthcare Human Again

2 minute read

Book title: Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol (Author)

  • URL

  • Enlightening, and insightful
  • Same author’s third book about the future of medicine

  • Author is a world-renowned cardiologist, Executive Vice-President of Scripps Research, founder of a new medical school and one of the top ten most cited medical researchers
  • He pointed out the transformational potential of AI for medicine , .is set to save time, lives and money.

  • a rough summary:
    • Dr. Topol tells us we are living in the Fourth Industrial Age, through AI ; AI has been sneaking into our lives;

    • The promise is to provide composite views of patients medical data; to improve decision support; to avoid error such as misdiagnosis and unnecesary procedures; to help in the ordering and interpretation of appropriate tests; and to recommend treatments;

    • For medicine, big datasets take the form of whole-genome sequences, high-res images, and continuous outputs from wearable sensors.

    • 3D Medicine: digitizing, and democratizing, and deep ;

    • *Propose three components of deep medicine: (1) deep phenotyping; (2) deep learning based pattern learning; (3) deep empathy and connection between doctors/health systems and patients. *

    • current medicine practice is Shallow medicine, indicated by e.g., physicians spending the majority time looking for information and only ~20 percent of time in talking with patients; doctors are overloaded with many duties not about caring patients at all; computer, keyboards screens, scans et al are pushing doctors away from close relationships with patients; Besides, current healthcare “is resulting in extraordinary waste, suboptimal outcomes, and unnecessary harm.”

    • Dr. Topol reviews the states of the art: AI is pushing progress in medicine on multiple narrow aspects; He also reviewed the DeepMind controversial beginning push in medicine due to the risk of privacy;

    • the author tried to connect self-driving cars and medicine in Chapter four; e.g., Five levels of self-driving (from no automation to full automation)

    • chapter6: doctors with patterns, e.g. 1. radiologiests are conducting pattern-centric practices; 2. pattern-heavy elements in other primary care and specialites include such as scans or slides,

    • clinicians without patterns: most physicians, nurses and clinicians do not have pattern-centric practices; their predominant function is making an assessment and formulating a plan. Here the author reviewed the IBM Waston efforts in medicine; reviewed a few potential areas of AI: eye doctor, cancer doctor, heart doctor, surgeon, and other healthcares like neurologists;

    • Dr. Topol devoted a whole chapter to discuss Mental health and potential of AI for it, especially the “no judgemental” chatbots.

    • Dr. Topol did a wonderful summary of cutting edge Deep learning efforts in life science and drug discovery

    • Dr. Topol used a whole chapter to survey Diet, nutrition and potential of AI in this important and messy field

    • AI for clinical output prediction and Virtual medical assitant through better input channels like Alexa…

    • Deep empathy: the last chapter deeplyl discuss the potential of using AI to save time in medicine, which will result in deep bonding between patients and doctors.