Many years ago, some classical AI expert systems claimed to outperform doctors in real-world tests. Never gained much traction. Explanations varied.
Personally, I am all for encoding medical knowledge in a machine-readable, open format knowledge base. I might even support requiring every journal article to provide input to it. Computers are designed for retrieving information and applying rules such as formal logic and Bayesian inference to filter and aggregate results. People are notorious for memory or logic lapses, especially under fatigue and other stress.
I can imagine an LLM-frontend might be vastly more doctor friendly than writing formal predicates for input or interpreting raw numbers for output. It could also provide a natural prompting system that recommends tests and warns of rare but serious alternative diagnoses.
Present AI tools can also look at data to suggest correlations that may merit research into improved treatment protocols.
I am strongly opposed to the idea of present-gen AI being used to supplant a formal knowledge base by "somehow" learning "better" than expert humans through unsupervised processing of existing texts and data. Such hubris seems endemic to AI hype.