|
|
|
|
|
|
by yarekt
4 days ago
|
|
|
I get it, and it draws parallels with debugging and incident response in software dev. Your best tool is good data, if you have more data, you’re able to make good judgement in short time. If AI helps you collect good data about your condition, then presenting that to a clinician is certainly better than “it hurts, idk” because there’s only so much they can do at the time |
|
|
Even for the part where she discovers she was in a caloric deficit and that carbs helped, the AI didn't seem to have a role:
> Figuring out what to track is an iterative process. At first, I logged only daily calories. But when I noticed that a small amount of carbs sometimes helped me recover faster mid-episode, I tracked carbs on the same spreadsheet.
The carb realization happened before tracking carbs. And why did it take a specialist to notice she was in a 300 calorie deficit? That seems like something that any AI process would trivially notice.
I don't know. This article is puzzling. I think using AI to analyze health records is interesting, but this article didn't really have anything supporting that other than to mention that she put everything into Claude on the side.