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Pneumoconiosis

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A comprehensive retrospect on the current perspectives and future prospects of pneumoconiosis.

Frontiers in public health
Pneumoconiosis is a widespread occupational pulmonary disease caused by inhalation and retention of dust particles in the lungs, is characterized by chronic pulmonary inflammation and progressive fibrosis, potentially leading to respiratory and/or he...

[A survey on the application of convolutional neural networks in the diagnosis of occupational pneumoconiosis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Pneumoconiosis ranks first among the newly-emerged occupational diseases reported annually in China, and imaging diagnosis is still one of the main clinical diagnostic methods. However, manual reading of films requires high level of doctors, and it i...

DLA-Net: dual lesion attention network for classification of pneumoconiosis using chest X-ray images.

Scientific reports
Accurate and early detection of pneumoconiosis using chest X-rays (CXR) is important for preventing the progression of this incurable disease. It is also a challenging task due to large variations in appearance, size and location of lesions in the lu...

AMFP-net: Adaptive multi-scale feature pyramid network for diagnosis of pneumoconiosis from chest X-ray images.

Artificial intelligence in medicine
Early detection of pneumoconiosis by routine health screening of workers in the mining industry is critical for preventing the progression of this incurable disease. Automated pneumoconiosis classification in chest X-ray images is challenging due to ...

Potential of digital chest radiography-based deep learning in screening and diagnosing pneumoconiosis: An observational study.

Medicine
The diagnosis of pneumoconiosis is complex and subjective, leading to inevitable variability in readings. This is especially true for inexperienced doctors. To improve accuracy, a computer-assisted diagnosis system is used for more effective pneumoco...

Deep Learning Models of Multi-Scale Lesion Perception Attention Networks for Diagnosis and Staging of Pneumoconiosis: A Comparative Study with Radiologists.

Journal of imaging informatics in medicine
Accurate prediction of pneumoconiosis is essential for individualized early prevention and treatment. However, the different manifestations and high heterogeneity among radiologists make it difficult to diagnose and stage pneumoconiosis accurately. H...

Diagnosis of Pneumoconiosis with Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Pneumoconiosis encompasses a group of lung diseases caused by inhaling dust particles. Frequently recognized as an occupational disease, it primarily affects workers in the mining industry. This paper details the use of machine learning algorithms to...

Deep learning pneumoconiosis staging and diagnosis system based on multi-stage joint approach.

BMC medical imaging
BACKGROUND: Pneumoconiosis has a significant impact on the quality of patient survival due to its difficult staging diagnosis and poor prognosis. This study aimed to develop a computer-aided diagnostic system for the screening and staging of pneumoco...

Attention-based multi-residual network for lung segmentation in diseased lungs with custom data augmentation.

Scientific reports
Lung disease analysis in chest X-rays (CXR) using deep learning presents significant challenges due to the wide variation in lung appearance caused by disease progression and differing X-ray settings. While deep learning models have shown remarkable ...

Clinical Validation of an AI System for Pneumoconiosis Detection Using Chest X-rays.

Journal of occupational and environmental medicine
OBJECTIVE: The aims of the study were to develop and evaluate "eTóraxLaboral," an intelligent platform for detecting signs of pneumoconiosis in chest radiographs and to assess its predictive capacity.