3 ms·

Machines will never replace dermatologists, machines will only make them more efficient.

djg123 7y ago
Well... Never say never. If you said machines would not replace dermatologists in the next 1 or 2 decades, I would agree with you. After that, all bets are off.
hhs 7y ago
Interesting point. The authors also seem to note this in their conclusion: “Our findings suggest that artificial intelligence algorithms may successfully assist dermatologists with melanoma detection in clinical practice which needs to be carefully evaluated in prospective trials.” They use the verb assist. I think this will be the case, tools like this will be made available to board certified dermatologists to enhance their work. It won’t replace them anytime soon. This field continues to be among the most competitive for physicians in the US. The barriers to entry are not only high, the number of residency spots get smaller each year when compared to total applicants. If interested, here’s some stats on med school rankings and derm match results: https://escholarship.org/uc/item/59p3z80r https://escholarship.org/uc/item/59p3z80r. But over many years I wonder what will happen. Will there be paradigm shifts that make us rethink about all these specialities and subspecialties? Should we combine them or do something else?
feral 7y ago
If you make a dermatologist 5x more efficient, don't you replace 80% of them? Or even better, allow them to spend more time on the hardest cases. And allow people with no access to a dermatologist now, access to a machine almost as good?
- sgt101 7y ago
  Actually when you make a knowledge worker / service worker in a business processes 5* more efficient the experience is that they spend 400% more time on the cases that they have left. These are the cases that you can't automate and that before automation you couldn't service properly/economically. Now you can, so the workers do.
rafiki6 7y ago
What is your efficiency metric here? Number of patients serviced? If so, it's not that simple. Imaging specialties might end up becoming more "efficient" (such as radiology), but medical patient data which is used to diagnose and triage is some of the worst there is (source: I worked with it). The only positive outcome I see from ML for the medical field for the foreseeable future might be to reduce the number of misdiagnoses if all things go very well.

Well... Never say never. If you said machines would not replace dermatologists in the next 1 or 2 decades, I would agree with you. After that, all bets are off.

hhs 7y ago

Interesting point. The authors also seem to note this in their conclusion: “Our findings suggest that artificial intelligence algorithms may successfully assist dermatologists with melanoma detection in clinical practice which needs to be carefully evaluated in prospective trials.” They use the verb assist. I think this will be the case, tools like this will be made available to board certified dermatologists to enhance their work. It won’t replace them anytime soon. This field continues to be among the most competitive for physicians in the US. The barriers to entry are not only high, the number of residency spots get smaller each year when compared to total applicants. If interested, here’s some stats on med school rankings and derm match results: https://escholarship.org/uc/item/59p3z80r https://escholarship.org/uc/item/59p3z80r. But over many years I wonder what will happen. Will there be paradigm shifts that make us rethink about all these specialities and subspecialties? Should we combine them or do something else?

feral 7y ago

If you make a dermatologist 5x more efficient, don't you replace 80% of them? Or even better, allow them to spend more time on the hardest cases. And allow people with no access to a dermatologist now, access to a machine almost as good?

sgt101 7y ago
Actually when you make a knowledge worker / service worker in a business processes 5* more efficient the experience is that they spend 400% more time on the cases that they have left. These are the cases that you can't automate and that before automation you couldn't service properly/economically. Now you can, so the workers do.

rafiki6 7y ago

What is your efficiency metric here? Number of patients serviced? If so, it's not that simple. Imaging specialties might end up becoming more "efficient" (such as radiology), but medical patient data which is used to diagnose and triage is some of the worst there is (source: I worked with it). The only positive outcome I see from ML for the medical field for the foreseeable future might be to reduce the number of misdiagnoses if all things go very well.