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Summary of Eric Topol's Deep Medicine
Summary of Eric Topol's Deep Medicine
Summary of Eric Topol's Deep Medicine
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Summary of Eric Topol's Deep Medicine

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#1 I had my left knee replaced when I was 62 years old. The surgeon said there was a 1 to 2 percent risk of infection, but I later learned that the pain from the surgery was beyond the reach of oxycodone. I became desperate for relief, and tried everything from acupuncture to electro-acupuncture to cold laser.

#2 The book Arthrofibrosis, which my wife found, explained that arthrofibrosis is a complication that occurs in 2 to 3 percent of patients after a knee replacement. It is a vicious inflammation response to the joint that results in profound scarring. I was warned about the risk of infection, but not about the risk of arthrofibrosis.

#3 AI is being used to help save lives already. My friend Dr. Stephen Kingsmore, a medical geneticist who heads up a pioneering program at the Rady Children’s Hospital in San Diego, was awarded a Guinness World Record for taking a sample of blood to a fully sequenced and interpreted genome in only 19. 5 hours.

#4 The key to saving this boy’s life was determining the root cause of his condition. Very experienced physicians might have eventually found the right course of treatment, but machines can do this work far quicker and better than people.

LanguageEnglish
PublisherIRB Media
Release dateJun 4, 2022
ISBN9798822529762
Summary of Eric Topol's Deep Medicine
Author

IRB Media

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    Summary of Eric Topol's Deep Medicine - IRB Media

    Insights on Eric Topol's Deep Medicine

    Contents

    Insights from Chapter 1

    Insights from Chapter 2

    Insights from Chapter 3

    Insights from Chapter 4

    Insights from Chapter 5

    Insights from Chapter 6

    Insights from Chapter 7

    Insights from Chapter 8

    Insights from Chapter 9

    Insights from Chapter 10

    Insights from Chapter 11

    Insights from Chapter 12

    Insights from Chapter 13

    Insights from Chapter 14

    Insights from Chapter 1

    #1

    I had my left knee replaced when I was 62 years old. The surgeon said there was a 1 to 2 percent risk of infection, but I later learned that the pain from the surgery was beyond the reach of oxycodone. I became desperate for relief, and tried everything from acupuncture to electro-acupuncture to cold laser.

    #2

    The book Arthrofibrosis, which my wife found, explained that arthrofibrosis is a complication that occurs in 2 to 3 percent of patients after a knee replacement. It is a vicious inflammation response to the joint that results in profound scarring. I was warned about the risk of infection, but not about the risk of arthrofibrosis.

    #3

    AI is being used to help save lives already. My friend Dr. Stephen Kingsmore, a medical geneticist who heads up a pioneering program at the Rady Children’s Hospital in San Diego, was awarded a Guinness World Record for taking a sample of blood to a fully sequenced and interpreted genome in only 19. 5 hours.

    #4

    The key to saving this boy’s life was determining the root cause of his condition. Very experienced physicians might have eventually found the right course of treatment, but machines can do this work far quicker and better than people.

    #5

    A patient’s history and exam raised the possibility that he might have heart disease. He had a blockage in his iliac artery to the left leg, and a CT scan with dye to map out his arteries showed that the right coronary artery was 80 percent narrowed. However, he felt energized right after the procedure was done.

    #6

    AI has been infiltrating our lives and medical practices for quite some time now. It is already prevalent in our daily experiences, from autocomplete when we type to unsolicited recommendations based on Google searches.

    #7

    There are many subtypes of AI. Traditionally, machine learning included logistic regression, Bayesian networks, Random Forests, support vector machines, expert systems, and many other tools for data analysis.

    #8

    The medical community was surprised by the abilities of deep learning AI, which has been able to diagnose some types of skin cancer better than board-certified dermatologists.

    #9

    Deep learning has been used in medicine to generate

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