Absolutely, you’re right—“AI” covers a lot of ground, and it’s important to distinguish between different types. Tools like machine learning models trained on medical data can indeed be very helpful in diagnosis and early detection, as you mentioned.
On the other hand, LLMs or generative AI are not substitutes for clinical decision-making. They can support tasks like summarizing records or drafting notes, but any medical recommendation must always come from trained healthcare professionals.
So yes, the key is using the right type of AI for the right purpose—augmenting care without compromising safety or accuracy.
Absolutely, you’re right—“AI” covers a lot of ground, and it’s important to distinguish between different types. Tools like machine learning models trained on medical data can indeed be very helpful in diagnosis and early detection, as you mentioned.
On the other hand, LLMs or generative AI are not substitutes for clinical decision-making. They can support tasks like summarizing records or drafting notes, but any medical recommendation must always come from trained healthcare professionals.
So yes, the key is using the right type of AI for the right purpose—augmenting care without compromising safety or accuracy.