Abstract: In one embodiment, computer implemented method identifies a risk of developing a condition for a particular patient. First, an initial variable set is developed by utilizing one or more patient databases. Second, an enhanced model predictive of a selected condition is created using machine learning. With the enhanced model developed, patient features vectors are created from a patient health information database for the initial variable set. The enhanced model is applied to these patient feature vectors to predict development of the condition. Patients predicted to have the condition can be enrolled in an appropriate intervention program.
Type:
Application
Filed:
April 21, 2017
Publication date:
October 26, 2017
Applicants:
NEW YORK UNIVERSITY, INDEPENDENCE BLUE CROSS
Inventors:
Narges Sharif Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith-McLallen, Somesh Nigam, David Sontag