AIMC Topic: Silicosis
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Rapid, non-invasive breath analysis for enhancing detection of silicosis using mass spectrometry and interpretable machine learning.
Journal of breath research
Mar 21, 2025
Occupational lung diseases, such as silicosis, are a significant global health concern, especially with increasing exposure to engineered stone dust. Early detection of silicosis is helpful for preventing disease progression, but existing diagnostic ...
Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study.
Frontiers in public health
Jan 15, 2025
OBJECTIVE: Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.
Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach.
Annals of global health
Jul 1, 2021
Although Artificial Intelligence (AI) is being increasingly applied, considerable distrust about introducing "disruptive" technologies persists. Intrinsic and contextual factors influencing where and how such innovations are introduced therefore requ...
Automated engineered-stone silicosis screening and staging using Deep Learning with X-rays.
Computers in biology and medicine
Jun 1, 2025
Silicosis, a debilitating occupational lung disease caused by inhaling crystalline silica, continues to be a significant global health issue, especially with the increasing use of engineered stone (ES) surfaces containing high silica content. Traditi...
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