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

ABSTRACT: Many real-world image recognition problems, such as diagnostic medical imaging exams, are "long-tailed" - 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 the research community on this emerging topic, we conducted an open challenge, CXR-LT, on long-tailed, multi-label thorax disease classification from chest X-rays (CXRs). We publicly release a l

SUBMITTER: Holste G 

PROVIDER: S-EPMC10659524 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature