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  • / <span>AI-based radiomic biomarkers to predict PD-(L)1 immune checkpoint inhibitor response within PD-L1 high/low/negative expression categories in stage IV NSCLC.</span>

AI-based radiomic biomarkers to predict PD-(L)1 immune checkpoint inhibitor response within PD-L1 high/low/negative expression categories in stage IV NSCLC.

Abstract Video & Slides Poster

Authors

George Simon

George R. Simon

H. Lee Moffitt Cancer Center and Research Institute, Celebration, FL

George R. Simon , Petr Jordan , Chiharu Sako , Ryan Beasley , Dwight Hall Owen , Arpan Patel , Brendan D. Curti , Roshanthi K. Weerasinghe , Soohee Lee , Arya Amini , An Liu , Ray D. Page , Aurélie Swalduz , Jean-Paul Beregi , Stéphane Sanchez , Olivier Gevaert , Ravi Bharat Parikh , Hugo Aerts

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Poster Details

Meeting

2023 ASCO Annual Meeting

Session Type

Poster Discussion Session

Session Title

Care Delivery and Regulatory Policy

Track

Care Delivery and Quality Care

Sub Track

Clinical Informatics/Advanced Algorithms/Machine Learning

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr 1517)

DOI

10.1200/JCO.2023.41.16_suppl.1517

Abstract #

1517

Poster Bd #

111

Abstract Disclosures

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