Enhancing Multi-Label Chest X-Ray Classification Using an Improved Ranking Loss

This article addresses the non-trivial problem of classifying thoracic diseases in chest X-ray (CXR) images. A single CXR image may exhibit multiple diseases, making this a multi-label classification problem. Additionally, the inherent class imbalance makes the task even more challenging as some dis...

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Bibliografiske detaljer

Principais autores:	Muhammad Shehzad Hanif, Muhammad Bilal, Abdullah H. Alsaggaf, Ubaid M. Al-Saggaf
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2025-05-01
Serier:	Bioengineering
Fag:	multi-label classification chest X-ray convolutional neural networks learning by ranking
Online adgang:	https://www.mdpi.com/2306-5354/12/6/593
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