Abstract: In some examples, data associated one or more medical presentations of a person is received. A mapping that associates the data to one or more candidate diagnoses is determined. The one or more candidate diagnoses correspond to one or more possible medical conditions associated with the person. A validation score for a first candidate diagnosis, of the one or more candidate diagnoses, is generated based on a set of features associated with the person. The validation score indicates an accuracy of the candidate diagnosis. At least partially in response to the generating of the validation score, an indicator is caused to be provided at a user device. The indicator indicates the validation score.

Abstract: In some examples, data associated one or more medical presentations of a person is received. A mapping that associates the data to one or more candidate diagnoses is determined. The one or more candidate diagnoses correspond to one or more possible medical conditions associated with the person. A validation score for a first candidate diagnosis, of the one or more candidate diagnoses, is generated based on a set of features associated with the person. The validation score indicates an accuracy of the candidate diagnosis. At least partially in response to the generating of the validation score, an indicator is caused to be provided at a user device. The indicator indicates the validation score.

Abstract: Methods, systems, and computer-readable media are disclosed herein for automatically identifying and selecting, based on machine learning model(s), one or more patient educations instructions as suggested smart recommendations for a particular patient, based on parameter matching and filtering with other patient parameters. The parameters of a current patient can be automatically matched to parameters that are associated with other patients, on a one-to-one parameter basis or based on specific combinations parameters. Based on the presence of one or more shared parameters between a current patient and other patients as well as the strength of the parameter match, one or more instructions that were provided to the other patients can be recommended for the current patient automatically. Instruction(s) selected for the current patient can then be stored in association with the parameters of the current patient and used to evaluate and make recommendations for subsequent patients.