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Artificial Intelligence–Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study

Sanja Đačić, William D. Travis, Jennifer M. Giltnane, Filip Kos, John H. Abel, Stephanie Hilz, Junya Fujimoto, Lynette M. Sholl, J. Ritter, Farah Khalil, Yi Liu, Amaro Taylor‐Weiner, Murray B. Resnick, Hui Yu, Fred R. Hirsch, Paul A. Bunn, David P. Carbone, Valerie W. Rusch, David J. Kwiatkowski, Bruce E. Johnson, Jay M. Lee, Stephanie Hennek, Ilan Wapinski, Alan Nicholas, Ann Johnson, Katja Schulze, Mark G. Kris, Ignacio I. Wistuba

2023Journal of Thoracic Oncology28 citationsDOIOpen Access PDF

Topics & Concepts

MedicineConcordanceHazard ratioReceiver operating characteristicNeoadjuvant therapyConfidence intervalGrading (engineering)Internal medicineOncologyRadiologyCancerBreast cancerCivil engineeringEngineeringAI in cancer detectionRadiomics and Machine Learning in Medical ImagingCutaneous Melanoma Detection and Management
Artificial Intelligence–Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study | Litcius