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  • 1294 External validation of machine learning models to predict efficacy and toxicity of immune checkpoint inhibitors using real-world pan cancer cohorts

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Regular and Young Investigator Award Abstracts
Machine Learning, Artificial Intelligence and Computational Modeling
1294 External validation of machine learning models to predict efficacy and toxicity of immune checkpoint inhibitors using real-world pan cancer cohorts

Authors

  • Zoltan Kiss Science and Technology Organization – Artificial Intelligence and Machine Learning, GE HealthCare, Budapest, Budapest, Hungary PubMed articlesGoogle scholar articles
  • Levente Lippenszky Science and Technology Organization – Artificial Intelligence and Machine Learning, GE HealthCare, Budapest, Budapest, Hungary PubMed articlesGoogle scholar articles
  • Balazs Laczi Science and Technology Organization – Artificial Intelligence and Machine Learning, GE HealthCare, Budapest, Budapest, Hungary PubMed articlesGoogle scholar articles
  • Pablo Napan-Molina Science and Technology Organization – Artificial Intelligence and Machine Learning, GE HealthCare, San Ramon, CA, USA PubMed articlesGoogle scholar articles
  • Eszter Csernai Science and Technology Organization – Artificial Intelligence and Machine Learning, GE HealthCare, Budapest, Budapest, Hungary PubMed articlesGoogle scholar articles
  • Alexander Brehmer Institute for AI in Medicine (IKIM), University Medicine Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Moon Kim Institute for AI in Medicine (IKIM), University Medicine Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Julius Keyl Institute for AI in Medicine (IKIM), University Medicine Essen, Essen, Nordrhein-Westfalen, Germany Institute of Pathology, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Jens Siveke German Cancer Consortium (DKTK), Partner Site Essen, Essen, Nordrhein-Westfalen, Germany Bridge Institute of Experimental Tumor Therapy (BIT), West German Cancer Center, University Hospital Essen (AöR), Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Moritz Meyer Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Essen, University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Viktor Grunwald Clinic for Medical Oncology, Clinic for Urology, West German Cancer Center, University Hospital Essen (AöR), Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Stefan Kasper German Cancer Consortium (DKTK), Partner Site Essen, Essen, Nordrhein-Westfalen, Germany Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Alexander Roesch German Cancer Consortium (DKTK), Partner Site Essen, Essen, Nordrhein-Westfalen, Germany Center for Medical Biotechnology (ZMB), University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany Department of Dermatology, University Hospital Essen, West German Cancer Center, University Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Martin Schuler German Cancer Consortium (DKTK), Partner Site Essen, Essen, Nordrhein-Westfalen, Germany Department of Medical Oncology, West German Cancer Center, University Hospital Essen (AöR), University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles
  • Travis Osterman Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA PubMed articlesGoogle scholar articles
  • Jan Wolber Pharmaceutical Diagnostics, GE HealthCare, Chalfont St Giles, Buckinghamshire, UK PubMed articlesGoogle scholar articles
  • Jens Kleesiek Institute for AI in Medicine (IKIM), University Medicine Essen, Essen, Nordrhein-Westfalen, Germany German Cancer Consortium (DKTK), Partner Site Essen, Essen, Nordrhein-Westfalen, Germany - Department of Physics, Technical University Dortmund, Dortmund, Nordrhein-Westfalen, Germany Cancer Research Center Cologne Essen (CCCE), West German Cancer Center Essen, Essen, Nordrhein-Westfalen, Germany PubMed articlesGoogle scholar articles

Citation

Kiss Z, Lippenszky L, Laczi B, et al
1294 External validation of machine learning models to predict efficacy and toxicity of immune checkpoint inhibitors using real-world pan cancer cohorts
Journal for ImmunoTherapy of Cancer 2023;11:doi: 10.1136/jitc-2023-SITC2023.1294
Online issue publication 
November 02, 2023

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© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.