Machine learning based on blood biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy

Zhou JG, Yang J, Wang H, Wong AHH, Tan F, Chen X, He S, Shen G, Wang YJ, Frey B, Fietkau R, Hecht M, Ma H, Gaipl U (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Annals of Oncology Elsevier

Publisher: ELSEVIER

City/Town: AMSTERDAM

Pages Range: S59-S59

Conference Proceedings Title: ANNALS OF ONCOLOGY

DOI: 10.1016/j.annonc.2022.02.069

Authors with CRIS profile

Rainer Fietkau Lehrstuhl für Strahlentherapie Markus Hecht Department of Radiation Oncology Udo Gaipl Department of Radiation Oncology

Involved external institutions

Zunyi Medical University CN China (CN) Guangdong Provincial People's Hospital CN China (CN) US National Institutes of Health (NIH) US United States (USA) (US) Harrisburg University of Science and Technology US United States (USA) (US) Sanofi-Aventis Groupe FR France (FR)

How to cite

APA:

Zhou, J.-G., Yang, J., Wang, H., Wong, A.H.-H., Tan, F., Chen, X.,... Gaipl, U. (2022). Machine learning based on blood biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy. In ANNALS OF ONCOLOGY (pp. S59-S59). AMSTERDAM: ELSEVIER.

MLA:

Zhou, J-G., et al. "Machine learning based on blood biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy." Proceedings of the ANNALS OF ONCOLOGY AMSTERDAM: ELSEVIER, 2022. S59-S59.

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