A5061385102- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Lung Cancer Diagnosis and Treatment
- Transplantation: Methods and Outcomes
- Hip disorders and treatments
- HER2/EGFR in Cancer Research
- Global Health Care Issues
- Pleural and Pulmonary Diseases
- Medical Imaging and Analysis
- Diabetic Foot Ulcer Assessment and Management
- Breast Lesions and Carcinomas
- Health, psychology, and well-being
- Phonocardiography and Auscultation Techniques
- Brain Metastases and Treatment
- Occupational and environmental lung diseases
- Health disparities and outcomes
- Esophageal and GI Pathology
- Cancer Cells and Metastasis
- Tracheal and airway disorders
- Gastrointestinal disorders and treatments
- Bone and Joint Diseases
Third People's Hospital of Hefei
2003-2025
Anhui Medical University
2022-2025
Background Chronic gastrointestinal disorders, such as chronic constipation and diarrhea, pose significant public health challenges, affecting quality of life healthcare costs. Life’s Simple 7 (LS7), established by the American Heart Association, encompasses essential behaviors that may influence bowel health. Methods We utilized data from National Health Nutrition Examination Survey (NHANES) conducted between 2005 2010, focusing on adults aged 20 years older. A total 12,912 participants...
Accurate prediction of pneumoconiosis is essential for individualized early prevention and treatment. However, the different manifestations high heterogeneity among radiologists make it difficult to diagnose stage accurately. Here, based on DR images collected from two centers, a novel deep learning model, namely Multi-scale Lesion-aware Attention Networks (MLANet), proposed diagnosis pneumoconiosis, staging screening I pneumoconiosis. A series indicators including area under receiver...
Early diagnosis and treatment of occupational pneumoconiosis can delay the development disease. This study is aimed at investigating intelligent by wavelet transform-derived entropy.From June 2013 to 2020, high KV digital radiographs (DR) computed tomography (CT) images from a total 60 patients with in our department were selected. The texture features extracted all images, decision tree was used for feature selection. support vector machines (SVM) three kernel functions selected classify...