Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge

Autor: Holste, Gregory, Zhou, Yiliang, Wang, Song, Jaiswal, Ajay, Lin, Mingquan, Zhuge, Sherry, Yang, Yuzhe, Kim, Dongkyun, Nguyen-Mau, Trong-Hieu, Tran, Minh-Triet, Jeong, Jaehyup, Park, Wongi, Ryu, Jongbin, Hong, Feng, Verma, Arsh, Yamagishi, Yosuke, Kim, Changhyun, Seo, Hyeryeong, Kang, Myungjoo, Celi, Leo Anthony, Lu, Zhiyong, Summers, Ronald M., Shih, George, Wang, Zhangyang, Peng, Yifan

Many real-world image recognition problems, such as diagnostic medical imaging exams, are "long-tailed" $\unicode{x2013}$ there are a few common findings followed by many more relatively rare conditions. In chest radiography, diagnosis is both a long

Externí odkaz: http://arxiv.org/abs/2310.16112

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge.

Autor: Holste G; Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, Austin, TX USA., Zhou Y; Department of Population Health Sciences, Weill Cornell Medicine, 10065, New York, NY USA., Wang S; Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, Austin, TX USA., Jaiswal A; Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, Austin, TX USA., Lin M; Department of Population Health Sciences, Weill Cornell Medicine, 10065, New York, NY USA., Zhuge S; School of Information Systems, Carnegie Mellon University, 15213, Pittsburgh, PA USA., Yang Y; Department of Electrical Engineering and Computer Science, Massachussetts Institute of Technology, 02139, Cambridge, MA USA., Kim D; School of Computer Science, Carnegie Mellon University, 15213, Pittsburgh, PA USA., Nguyen-Mau TH; University of Science, VNU-HCM, 70000, Ho Chi Minh City, Vietnam., Tran MT; University of Science, VNU-HCM, 70000, Ho Chi Minh City, Vietnam., Jeong J; KT Research & Development Center, KT Corporation, 06763, Seoul, South Korea., Park W; Department of Software and Computer Engineering, Ajou University, 16499, Suwon, South Korea., Ryu J; Department of Software and Computer Engineering, Ajou University, 16499, Suwon, South Korea., Hong F; Cooperative Medianet Innovation Center, Shanghai Jiao Tong University, 200240, Shanghai, China., Verma A; Wadhwani Institute for Artificial Intelligence, 400079, Mumbai, India., Yamagishi Y; Division of Radiology and Biomedical Engineering, Graduate School of Medicine, The University of Tokyo, 113-0033, Tokyo, Japan., Kim C; BioMedical AI Team, AIX Future R&D Center, SK Telecom, 04539, Seoul, South Korea., Seo H; Interdisciplinary Program in AI (IPAI), Seoul National University, 02504, Seoul, South Korea., Kang M; Department of Mathematical Sciences, Seoul National University, 02504, Seoul, South Korea., Celi LA; Laboratory for Computational Physiology, Massachusetts Institute of Technology, 02139, Cambridge, MA USA.; Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, 02215, Boston, MA USA.; Department of Biostatistics, Harvard T.H. Chan School of Public Health, 02115, Boston, MA USA., Lu Z; National Center for Biotechnology Information, National Library of Medicine, 20894, Bethesda, MD USA., Summers RM; Clinical Center, National Institutes of Health, 20892, Bethesda, MD USA., Shih G; Department of Radiology, Weill Cornell Medicine, 10065, New York, NY USA., Wang Z; Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, Austin, TX USA., Peng Y; Department of Population Health Sciences, Weill Cornell Medicine, 10065, New York, NY USA.

Publikováno v: ArXiv [ArXiv] 2024 Apr 01. Date of Electronic Publication: 2024 Apr 01.