Join to access to all OVN content. Join for Free
New Machine Learning Framework Uses EHR Data to Assess ICI Effectiveness, Toxicity

New Machine Learning Framework Uses EHR Data to Assess ICI Effectiveness, Toxicity


Share This Article


Drs. Shaalan Beg and Travis Osterman discuss a machine learning model, recently featured in JCO Clinical Cancer Informatics, that uses electronic health record data to accurately predict the effectiveness and toxicity of treatment with immune checkpoint inhibitors. The new AI model can be used to provide a personalized risk-benefit profile, inform therapeutic decision-making, and improve clinical trial cohort selection.

Click for Source

Related Topics

Meet Our Innovation Partners

Loading partners...

You May Also Like

Article
Virtual Clinical Trials in Oncology-Overview, Challenges, Policy Considerations, and Future Directions
OVN Avatar Kushal T. Kadakia, MSc, Malke Asaad, MD, Erica Adlakha, MS, Michael J. Overman, MD, Cristina M. Checka, MD, and Anaeze C. Offodile II, MD, MPH

Virtual Clinical Trials in Oncology-Overview, Challenges, Policy Considerations, and Future Directions

Article
Comparative study on anticancer drug access times between FDA, EMA and the French temporary authorisation for use program over 13 years
OVN Avatar Emmanuelle Jacqueta, Ghania Kerouani-Lafayeb, Francoise Grudeb, Sergio Goncalvesb, Annie Lorenced, Florence Turcryb, Liora Brunelb, Laetitia Belgodereb, Adrien Monardc, Gaëlle Guyaderb, Lotfi Boudalib, Nicolas Albin

Comparative study on anticancer drug access times between FDA, EMA and the French temporary authorisation for use program over 13 years

Article
Evaluation of Trials Comparing Single-Enantiomer Drugs to Their Racemic Precursors: A Systematic Review
OVN Avatar Aaron S. Long, BS; Audrey D. Zhang, MD; Caitlin E. Meyer, MLIS; Alexander C. Egilman, BS; Joseph S. Ross, MD, MHS; Joshua D. Wallach, PhD, MS

Evaluation of Trials Comparing Single-Enantiomer Drugs to Their Racemic Precursors: A Systematic Review

Article
Transforming oncology: Five frontiers driving progress in cancer care
Partner Avatar iNIZIO

Transforming oncology: Five frontiers driving progress in cancer care

Article
Virtual Oncology MSL Team Increases KOL Engagement by 120%
Partner Avatar iNIZIO

Virtual Oncology MSL Team Increases KOL Engagement by 120%

Article
Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis
OVN Avatar Jayson L. Parker, Sebnem S. Kuzulugil, Kirill Pereverzev, Stephen Mac, Gilberto Lopes, Zain Shah, Ashini Weerasinghe, Daniel Rubinger, Adam Falconi, Ayse Bener, Bora Caglayan, Rohan Tangri, Nicholas Mitsakakis

Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis

Explore OVN