Journal
DIAGNOSTICS
Volume 11, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/diagnostics11040694
Keywords
artificial intelligence; computer-aided diagnosis system; deep learning; esophageal lesion; gastric lesion; gastrointestinal endoscopy; intestinal lesion
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Funding
- National Key Research and Development Program of China [2019YFB1311300]
- Ningbo Project [2019C50052]
- Nottingham Project [NCHI I01200100023]
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This study discussed the application prospects of CAD system based on deep learning in the medical field and its importance in clinical practice, and also proposed some prospects for future research directions.
At present, the application of artificial intelligence (AI) based on deep learning in the medical field has become more extensive and suitable for clinical practice compared with traditional machine learning. The application of traditional machine learning approaches to clinical practice is very challenging because medical data are usually uncharacteristic. However, deep learning methods with self-learning abilities can effectively make use of excellent computing abilities to learn intricate and abstract features. Thus, they are promising for the classification and detection of lesions through gastrointestinal endoscopy using a computer-aided diagnosis (CAD) system based on deep learning. This study aimed to address the research development of a CAD system based on deep learning in order to assist doctors in classifying and detecting lesions in the stomach, intestines, and esophagus. It also summarized the limitations of the current methods and finally presented a prospect for future research.
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