{"paper":{"title":"Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ajay Jaiswal, Arsh Verma, Changhyun Kim, Dongkyun Kim, Feng Hong, George Shih, Gregory Holste, Hyeryeong Seo, Jaehyup Jeong, Jongbin Ryu, Leo Anthony Celi, Mingquan Lin, Minh-Triet Tran, Myungjoo Kang, Ronald M. Summers, Sherry Zhuge, Song Wang, Trong-Hieu Nguyen-Mau, Wongi Park, Yifan Peng, Yiliang Zhou, Yosuke Yamagishi, Yuzhe Yang, Zhangyang Wang, Zhiyong Lu","submitted_at":"2023-10-24T18:26:22Z","abstract_excerpt":"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-tailed and multi-label problem, as patients often present with multiple findings simultaneously. While researchers have begun to study the problem of long-tailed learning in medical image recognition, few have studied the interaction of label imbalance and label co-occurrence posed by long-tailed, multi-label disease classification. To engage with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.16112","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2310.16112/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}