Article

A diagnostic support system based on interpretable machine learning and oscillometry for accurate diagnosis of respiratory dysfunction in silicosis

2025-01-13

Abstract excerpt

<h4>ABSTRACT</h4> Silicosis, the most dangerous and common lung illness associated with breathing in mineral dust, is a significant health concern. Spirometry, the traditional method for evaluating pulmonary functions, requires high patient compliance. Respiratory Oscillometry and electrical models are being studied to evaluate the respiratory system. This study aims to harness the power of machine learning (ML)...

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Literature Corpus work: ba0221fb-8757-5fd2-9c6e-75f935fcdc43
DOI: 10.1101/2025.01.08.632001

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