In building clinical AI, one thing you deal with is making sure the clinician considers all possible differentials without overwhelming them with caveats and exceptions. Most people attach likelihood percentages to each diagnosis, with the least likely receiving the lowest percentage. The problem with that is that LLMs are not good at calibration, so an LLM showing a likelihood of 5% may not really represent a statistical likelihood of 5% for the particular patient, given all the context, including the contexts the AI does not see or account for, like environment, demography, local epidemiology, etc. Attaching context to each differential is helpful. But for a physician short on time, too much context can become another load they have to manage. One method I use is to include the diagnoses that could be fatal at the top, even if the probability of them is low. Bringing them to the physician's conscious mind could also help them think more critically about whether they could be missing something important themselves.