A Predictive AI Model for Identifying Slow Progressors Among aNSCLC Patients

Senior Machine Learning Engineer, Francois Charest, PhD, presents findings from a novel predictive AI model that was developed by Concerto engineers focused on "exceptional responders," given that there are few predictors known of extreme treatment response. In this research abstract accepted at ASCO 2020 Virtual Scientific Program, Dr. Charest shares researchers' findings for predicting slow progression in NSCLC patients using Machine Learning and large-scale real-world data based on CancerLinQ's oncology EMR data linked to claims and progression assessments curated by Concerto’s expert oncology nurses.

Francois_Slow Progressors_asco abstract video