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by neuro_image3
2361 days ago
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I wasn't just commenting on the abstract presented. I was commenting on the comments I see here, as well as comments I see related to similar papers all the time. I also interact with AI/ML researchers all the time. Most of them are typically some combination of:
1. Poorly informed about the appropriate context and utility of medical imaging.
2. Trying as hard as they can to push AI/ML as the most important technology in medicine today.
3. Pursuing a very task-specific project which they claim is massively generalizable in some (incorrect) way. |
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My engineering mind just can't come up to terms with this. Why wouldn't you collect all information you possibly can? You can always ignore irrelevant data you have, but you cannot consider data that you don't have!
The closest I've been to rationalizing this: diagnosing is a stochastic process so complex (and with the search space so large) that the random noise in extra data is likely to point you towards wrong directions. Plus you can always collect more data afterwards if your initial diagnosis turns out to be wrong. This is of course very simplified, but it makes sense.
However, I just can't turn off my inner voice from screaming "more data is always better". I guess that's why I'm not an MD :)