Georgetown University

Carnegie Mellon University

Hao-Ren Yao

Ophir Frieder

Der-Chen Chang

Chenyan Xiong

Liwen Sun

Embodiments of the present systems and methods may provide techniques to predict the success or failure of a drug used for disease treatment. For example, a method of determining drug efficacy may include, for a plurality of patients, generating a directed acyclic graph from health related information of each patient comprising nodes representing a medical event of the patient, at least one first edge connecting the first node to an additional node, each additional edge connecting nodes representing two consecutive medical events, the edge having a weight based on a time difference between the two consecutive medical events, capturing a plurality of features from each directed acyclic graph, generating a binary graph classification model on captured features of each directed acyclic graph, determining a probability that a drug or treatment will be effective using the binary graph classification model, and determining a drug to be prescribed to a patient based on the determined probability.

Method and system for assessing drug efficacy using multiple graph kernel fusion

Systems and processes described herein are for monitoring data records and predicting changes to coded values in the data records. More specifically, this disclosure relates to predicting and potentially preventing anomalies represented in data records by predicting values of entries to be added to the data records and causing a prophylactic response to the predicted anomaly to prevent the anomaly from occurring.

Growing community of inventors

McLean, VA, United States of America

Hao-Ren Yao