Evidence map›Paper›PMID 40735106›Full record

ArticleArXiv2025

CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray.

Mingquan Lin, Gregory Holste, Song Wang, Yiliang Zhou, Yishu Wei, Imon Banerjee, Pengyi Chen, Tianjie Dai, Yuexi Du, Nicha C Dvornek and 23 more

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

33 authors.

Mingquan LinDepartment of Surgery, University of Minnesota, Minneapolis, USA.
Gregory HolsteDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, USA.
Song WangDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, USA.
Yiliang ZhouDepartment of Population Health Sciences, Weill Cornell Medicine, New York, USA.
Yishu WeiDepartment of Population Health Sciences, Weill Cornell Medicine, New York, USA.
Imon BanerjeeDepartment of Radiology, Mayo Clinic, Phoenix, USA.
Pengyi ChenCooperative Medianet Innovation Center, Shanghai Jiao Tong University, Shanghai, China.
Tianjie DaiCooperative Medianet Innovation Center, Shanghai Jiao Tong University, Shanghai, China.
Yuexi DuDepartment of Biomedical Engineering, Yale University, New Haven, USA.
Nicha C DvornekDepartment of Biomedical Engineering, Yale University, New Haven, USA.
Yuyan GeCenter for Innovation in Data Engineering and Science, Department of Computer and Information Science, University of Pennsylvania, Philadelphia, USA.
Zuwei GuoSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, USA.
Shouhei HanaokaDepartment of Radiology, The University of Tokyo Hospital, Tokyo, Japan.
Dongkyun KimSchool of Computer Science, Carnegie Mellon University, Pittsburgh, USA.
Pablo MessinaPontificia Universidad Católica de Chile, Santiago, Chile.
Yang LuSchool of Informatics, Xiamen University, Xiamen, China.
Denis ParraPontificia Universidad Católica de Chile, Santiago, Chile.
Donghyun SonSeoul National University, Seoul, South Korea.
Álvaro SotoPontificia Universidad Católica de Chile, Santiago, Chile.
Aisha UroojDepartment of Radiology, Mayo Clinic, Phoenix, USA.
René VidalCenter for Innovation in Data Engineering and Science, Departments of Electrical and Systems Engineering & Radiology, University of Pennsylvania, Philadelphia, USA.
Yosuke YamagishiDepartment of Radiology, The University of Tokyo Hospital, Tokyo, Japan.
Zefan YangDepartment of Biomedical Engineering and Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA.
Ruichi ZhangSchool of Informatics, Xiamen University, Xiamen, China.
Yang ZhouInstitute of High Performance Computing, A*STAR, Singapore.
Leo Anthony CeliLaboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, USA.
Ronald M SummersClinical Center, National Institutes of Health, Bethesda, USA.
Zhiyong LuNational Center for Biotechnology Information, National Library of Medicine, Bethesda, USA.
Hao ChenDepartment of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China.
Adam FlandersDepartment of Radiology, Thomas Jefferson University Hospital, Philadelphia, USA.
George ShihDepartment of Population Health Sciences, Weill Cornell Medicine, New York, USA.
Zhangyang WangDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, USA.
Yifan PengDepartment of Population Health Sciences, Weill Cornell Medicine, New York, USA.

Funding

Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AIOT2OD032701 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI BIHORAC, AZRA, CLERMONT, GILLES · 2022 to 2025
$24.6M
MUST Data Science Research Hub (MUDSReH) - Democratized Trusted Research Environment (dTRE)U54TW012043 · FIC · MBARARA UNIVERSITY/SCIENCE/ TECHNOLOGY · PI Leo Anthony G Celi, Jessica Elizabeth Haberer · 2021 to 2026
$6.9M
Critical Care Informatics: Ethical considerations around the use and sharing of health-related dataR01EB017205 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI CELI, LEO ANTHONY G, MARK, ROGER GREENWOOD · 2014 to 2021
$3.8M
Closing the loop with an automatic referral population and summarization systemR01LM014306 · NLM · WEILL MEDICAL COLL OF CORNELL UNIV · PI Yifan Peng, Justin Frederick Rousseau · 2023 to 2026
$2.7M
FIC NIH HHS U54 TW012043NIBIB NIH HHS R01 EB017205NIH HHS OT2 OD032701NLM NIH HHS R01 LM014306
6 · The paper itself

Abstract

The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges in open long-tailed lung disease classification and enhances the measurability of state-of-the-art techniques. The first event, CXR-LT 2023, aimed to achieve these goals by providing high-quality benchmark CXR data for model development and conducting comprehensive evaluations to identify ongoing issues impacting lung disease classification performance. Building on the success of CXR-LT 2023, the

Indexed as

Chest X-rayComputer-aided diagnosisLong-tailed learningzero-shot learning

Identifiers

PMID40735106
PMCPMC12306832

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.