One clinical foundation model, two ways to predict: representations win on risk, generation wins on same-day orders
FERMAT, a 65-million-parameter clinical foundation model pretrained on records from 3.77 million patients, was compared against itself on the same patients: patient representations predicted five-year kidney, fatty liver, and diabetes risk better, while generated trajectories predicted the diagnoses, prescriptions, and procedures recorded together on the next clinical date better.