Presenting “Automatic Identification of Oncology Patients” at ASCO 2022

Venue: McCormick Place, Chicago, IL, USA

The results of our collaboration with leading US oncologists from the largest healthcare systems, titled “Automatic Identification of Oncology Patients with Unsupervised Phenotyping and AutoML”, has been accepted at the annual American Society of Clinical Oncology (ASCO) meeting.

Recent studies suggest International Classification of Diseases (ICD) codes often cannot characterize patients with specific diseases like oncology accurately in real-world clinical practice due to a high probability of miscoding, while manual inspection of millions of patients is not feasible as it is highly costly and slow. Therefore, we present an AI driven workflow, which leverages both structured discrete values and unstructured textual data from Electronic Health Records (EHRs), to automatically identify cancer patients especially those who might be miscoded or undiagnosed.

Request Abstract

Attendees

Dr. VK Gadi

Director of Medical Oncology, UI Health;
Associate Director, University of Illinois Cancer Center

Dr. Vibhor Gupta

Founder
Pangaea Data