"Promising development in the fight with cancer using artificial intelligence" with a new privacy-preserving approach named MEDomics

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University of California - San Francisco

Jul 22, 2021, 11:31 ET

SAN FRANCISCO, July 22, 2021 /PRNewswire/ -- Published first in Nature Cancer, "MEDomics" refers to a novel approach using hospital based medical notes to refine predictions and prognosis in cancer patients over time.

Their work is available in open-access at
https://www.nature.com/articles/s43018-021-00236-2

An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication

"We reported results of the first longitudinal approach to natural language processing of unstructured medical notes and demonstrate its ability to update and improve a prognostic model over time, as a patient's oncologic illness course unfolds," said Olivier Morin, leader of the project and head of the physics division at UCSF. The work was pioneered at UCSF, and is the result of a collaboration among an international consortium comprising U.S., (UCSF, San Francisco) Canadian (McGill, Université de Sherbrooke, Montreal) and European centers (Oncoray in Dresden and Maastricht University).

Catherine Park, M.D. Co-senior author and Chair of the department of Radiation Oncology at UCSF added: "With this data we were able to validate findings of published clinical trials using real world data, e.g. the positive impact of immunotherapy in lung cancer. In addition, there are exciting opportunities to generate hypothesis based on associations from patients' individual health profiles, and risk factors."

Professor Phillippe Lambin senior author and Chair of the department of Precision Medicine at Maastricht University adds, "The MEDomics infrastructure allowed us to validate several new clinical hypotheses like the importance of cardio-vascular morbidity for the outcome of cancer treatment."

The consortium has created a secure, dynamic, continuously learning and expandable infrastructure, termed MEDomics, designed to constantly capture multimodal electronic health information, including imaging, across a large and multicentric healthcare system (watch the animation: https://youtu.be/2030Pdgm3_4).

Dr. Morin and collaborators added, now part of the code is open source and we would like to expand the international consortium (visit www.medomics.ai). “Our vision is to create an open-source computation platform integrating all MEDomics developments and from which both clinical staff and research scientists could tackle a diverse range of oncological problems using AI”.

Contact: Dr. Olivier Morin PhD, [email protected] , +14153089257

SOURCE University of California - San Francisco