Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers.

Journal: Frontiers in immunology
Published Date: Dec 1, 2022

Abstract

INTRODUCTION: Despite the many benefits immunotherapy has brought to patients with different cancers, its clinical applications and improvements are still hindered by drug resistance. Fostering a reliable approach to identifying sufferers who are sensitive to certain immunotherapeutic agents is of great clinical relevance.

Authors

  • Wenyi Jin
    Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan 430060, China.
  • Qian Yang
    Center for Advanced Scientific Instrumentation, University of Wyoming, Laramie, WY, United States.
  • Hao Chi
    University of Chinese Academy of Sciences , Beijing, China.
  • Kongyuan Wei
    Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
  • Pengpeng Zhang
    Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, USA; Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, USA. Electronic address: zhangp@mskcc.org.
  • Guodong Zhao
    Faculty of Hepatopancreatobiliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
  • Shi Chen
    Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, PUMCH, CAMS & PUMC, Beijing, China.
  • Zhijia Xia
    Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany.
  • Xiaosong Li
    School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100083, China.

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