Journal of Ayub Medical College, Abbottabad : JAMC
38404098
Anthracosis is a type of mild pneumoconiosis secondary to harmless carbon dust deposits. Although anthracosis was previously associated with inhaled coal particles, such as coal workers' pneumoconiosis, this hypothesis was later abandoned; pathology ...
OBJECTIVES: To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists.
This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pneumoconiosis screening and staging using chest radiographs. The model, based on chest radiographs, was developed using a training cohort and validated ...
International journal of environmental research and public health
34501684
Pneumoconiosis remains one of the most common and harmful occupational diseases in China, leading to huge economic losses to society with its high prevalence and costly treatment. Diagnosis of pneumoconiosis still strongly depends on the experience o...
PURPOSE: The objective of this study is to construct a computer aided diagnosis system for normal people and pneumoconiosis using X-raysand deep learning algorithms.
PURPOSE: This paper aims to develop a successful deep learning model with data augmentation technique to discover the clinical uniqueness of chest X-ray imaging features of coal workers' pneumoconiosis (CWP).
IEEE journal of biomedical and health informatics
35834466
Pneumoconiosis staging has been a very challenging task, both for certified radiologists and computer-aided detection algorithms. Although deep learning has shown proven advantages in the detection of pneumoconiosis, it remains challenging in pneumoc...
BACKGROUND: This study aims to explore appropriate model for predicting the disease burden of pneumoconiosis in Tianjin by comparing the prediction effects of Autoregressive Integrated Moving Average (ARIMA) model, Deep Neural Networks (DNN) model an...
Computer methods and programs in biomedicine
38215580
OBJECTION: The aim of this study is to develop an early-warning model for identifying high-risk populations of pneumoconiosis by combining lung 3D images and radiomics lung texture features.