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Artificial intelligence in gastroenterology: where are we heading?
- Source :
- Frontiers of Medicine. 14:511-517
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Artificial intelligence (AI) is coming to medicine in a big wave. From making diagnosis in various medical conditions, following the latest advancements in scientific literature, suggesting appropriate therapies, to predicting prognosis and outcome of diseases and conditions, AI is offering unprecedented possibilities to improve care for patients. Gastroenterology is a field that AI can make a significant impact. This is partly because the diagnosis of gastrointestinal conditions relies a lot on image-based investigations and procedures (endoscopy and radiology). AI-assisted image analysis can make accurate assessment and provide more information than conventional analysis. AI integration of genomic, epigenetic, and metagenomic data may offer new classifications of gastrointestinal cancers and suggest optimal personalized treatments. In managing relapsing and remitting diseases such as inflammatory bowel disease, irritable bowel syndrome, and peptic ulcer bleeding, convoluted neural network may formulate models to predict disease outcome, enhancing treatment efficacy. AI and surgical robots can also assist surgeons in conducting gastrointestinal operations. While the advancement and new opportunities are exciting, the responsibility and liability issues of AI-assisted diagnosis and management need much deliberations.
- Subjects :
- medicine.medical_specialty
Disease outcome
Conventional analysis
Scientific literature
Gastroenterology
03 medical and health sciences
0302 clinical medicine
Artificial Intelligence
Internal medicine
medicine
Humans
Irritable bowel syndrome
business.industry
General Medicine
Prognosis
medicine.disease
Treatment efficacy
030220 oncology & carcinogenesis
Medicine public health
030211 gastroenterology & hepatology
Neural Networks, Computer
Artificial intelligence
Peptic ulcer bleeding
business
Surgical robot
Subjects
Details
- ISSN :
- 20950225 and 20950217
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- Frontiers of Medicine
- Accession number :
- edsair.doi.dedup.....0084d02d403e30ecbe4dd0df989bd19c