Relevance feedback to improve the performance of clustering model that clusters patients with similar profiles together

Abstract

In patient cohort identification, clustering () of patients is performed using a patient comparison metric dependent on a set of features (). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster () containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations () each plotting the sample patients and the query patient against two or more features of the modality.