Will Robots replace Doctors?

 Case Study




       A  2017 study out of the Massachusetts General Hospital and MIT showed that an artificial intelligence (AI) system was equal or better than radiologists at reading mammograms for high risk cancer lesions needing surgery. A year earlier, and reported by the Journal of the American Medical Association, Google showed that computers are similar to ophthalmologists at examining retinal images of diabetics.  And recently, computer-controlled robots performed intestinal surgery successfully on a pig. While the robot took longer than a human, its sutures were much better more precise and uniform with fewer chances for breakage, leakage, and infection. Tech boosters believe that AI will lead to more evidence-based care, more personalized care, and fewer errors.

Of course, improving diagnostic and therapeutic outcomes are laudable goals. But AI is only as good as the humans programming it and the system in which it operates. If we are not careful, AI could not make health care better, but instead unintentionally exacerbate many of the worst aspects of our current health care system.



Using deep and machine learning, AI systems analyze enormous amounts of data to make predictions and recommend interventions. Advances in computing power have enabled the creation and cost-effective analysis of large datasets of payer claims, electronic health record data, medical images, genetic data, laboratory data, prescription data, clinical emails, and patient demographic information to power AI models.

AI is 100 percent dependent on this data, and as with everything in computing, “garbage in, garbage out,” as the saying goes. A major concern about all our health care datasets is that they perfectly record a history of unjustified and unjust disparities in access, treatments, and outcomes across the United States.



Comments

  1. UnknownMarch 22, 2022 at 4:12 AM

    It will surely take time.

    ReplyDelete
  2. UnknownMarch 22, 2022 at 11:29 AM

    No doubt this buzzowd AI is making headlines in medical field, but it is challenging as well. As you said that it relies on data, in itself is a limitation for AI. Not much amount of data is available for recent diseases like Alzheimer's and Parkinson's. Even in wet lab research, there is always scarcity for the subjects to test a potential drug.
    It becomes even more challenging when the appearance of any medical condition is not consistent with the available data. As in the case of Covid-19, with enormous data available, we are not being able to predict the structure of spike proteins in upcoming strains. Yes, AI is definitely going to help enormously in medical field as you mentioned, but I see AI as an assistance rather than a mastery or replacement of humans as of now.

    ReplyDelete

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