Quantitative computed tomography imaging classification of cement dust-exposed patients-based Kolmogorov-Arnold networks.
Journal:
Artificial intelligence in medicine
Published Date:
May 27, 2025
Abstract
BACKGROUND: Occupational health assessment is critical for detecting respiratory issues caused by harmful exposures, such as cement dust. Quantitative computed tomography (QCT) imaging provides detailed insights into lung structure and function, enhancing the diagnosis of lung diseases. However, its high dimensionality poses challenges for traditional machine learning methods.
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