Machine learning enabled patient stratification

A system, comprising:

• at least one data processor;
• and
• at least one memory storing instructions, which when executed by the at least one data processor, result in operations comprising:
• applying a first machine learning model to determine, based at least on a clinical data of a patient, a risk score for the patient;
• in response to the risk score for the patient exceeding a first threshold, applying a second machine learning model to determine a first probability of the risk score being a false positive;
• in response to the risk score for the patient failing to exceed the first threshold, applying a third machine learning model to determine a second probability of the risk score being a false negative;
• and
• determining, based at least on the risk score, the first probability of the risk score being the false positive, and the second probability of the risk score being the false negative, one or more clinical recommendations for the patient.