I recently read a paper on AI for early lung cancer diagnosis, which reported 98% accuracy on a specific dataset. However, I've also heard that when used in actual hospitals, performance can drop due to data bias or environmental differences.
For example, some studies show that AI for skin cancer diagnosis in dermatology is optimized for white skin, leading to higher misdiagnosis rates for Asian patients.
I'm curious about how trustworthy medical AI is in real clinical settings, and how regulatory and ethical issues will be addressed going forward. I'd love to hear opinions from people working in this field.
The accuracy of medical AI heavily depends on the dataset. A figure like 98% is often achieved in controlled environments, but in real clinical settings, it can drop to 70-80% due to factors such as patient diversity, image quality, and equipment differences. Models lacking sufficient Asian data, in particular, require caution.
by 카페인중독992 · ▲0