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Comment by dontreact | Hacker News Reader

I think you are not being creative enough about how AI can influence medical care, and also not aware of existing deployed solutions making significant clinical impact.

For example, viz.ai has a solution to help get brain bleeds spotted to the eyes of surgeons more quickly. It is deployed and has cut the average length of stay in the neuro ICU significantly

https://mobile.twitter.com/viz_ai/status/1314710308603133953

I work at Caption Health, where we are enabling novices to take echocardiography scans. The doctors who work with our technology found it extremely useful to help diagnose cardiac involvement during covid.

https://captionhealth.com/education/

As much as I have respect for the expertise of medical doctors, I would ask that you have respect for folks working to apply AI in medicine.

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Hi, I did not intend to be disrespectful, sorry if you read my message like this.

I mainly intended to underline the fact that we (doctors) were promised a revolution in healthcare (AKA : to disappear) and we ended with diagnostic scores.

However, I gladly admit that I exaggerated and that AI technologies can be helpful in some cases, of course.

Geoffrey Hinton really made things hard for folks on the AI side and even walked back that promise.

I think it’s the classic thing where it’s overestimated in the short term and underestimated in the long (longggg) term.

My sense is that for AI to have the full impact it will one day reach, it will take rethinking medical care entirely with online machine learning and data at the core of how decisions are made.

ML was able to revolutionize how ads are delivered (for better or worse, but at least reaching the objectives of those who deployed it) because you can update and deploy the models multiple times a day.

If we can one day get to a world like that where an ML mode is constantly learning and updating itself, and has seen far more patients than any individual doctor, then maybe we will see the sorts of bigger shifts that were imagined shortly after we started to see ML surpass human ability on long standing difficult tasks like object recognition.

Getting there is a long, long road where we need to learn to work together with AI and figure out where the holes are in terms of robustness, earn trust over years of successful deployment, and figure out how to properly put safety bounds around more frequent updates to models.

I agree on the very long term possibilities. However, the first problem to solve is the data collection. Saving doctors and nurses from their horrible professional softwares and replacing them with user-friendly, well-thought, data collection friendly softwares would be a huge step forward.

There are certainly tons of people working on this. I think that the entrenched competitors will only be displaced by other folks who are achieving things they cannot via AI. These two problems are closely linked for sure.

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