Comprehensive Computer-Aided Decision Support Framework to Diagnose Tuberculosis From Chest X-Ray Images: Data Mining Study.
Muhammad OwaisMuhammad ArsalanTahir MahmoodYu Hwan KimKang Ryoung ParkPublished in: JMIR medical informatics (2020)
This paper presents a comprehensive CAD framework to diagnose TB from CXR images by retrieving the relevant cases and their clinical observations from the previous patients' database. These retrieval results assist the radiologist in making an effective diagnostic decision related to the current medical condition of a patient. Moreover, the retrieval results can facilitate the radiologists in subjectively validating the CAD decision.
Keyphrases
- coronary artery disease
- mycobacterium tuberculosis
- end stage renal disease
- deep learning
- convolutional neural network
- newly diagnosed
- artificial intelligence
- decision making
- prognostic factors
- electronic health record
- peritoneal dialysis
- case report
- high resolution
- emergency department
- magnetic resonance imaging
- big data
- magnetic resonance
- pulmonary tuberculosis
- dual energy