Gastrointestinal diseases are increasing in global prevalence. As a result, the contribution to both mortality and healthcare costs is increasing. While interventions utilizing scoping techniques or ultrasound are crucial to both the timely diagnosis and management of illness, a few limitations are associated with these techniques. Artificial intelligence, using computerized diagnoses, deep learning systems, or neural networks, is increasingly being employed in multiple aspects of medicine to improve the characteristics and outcomes of these tools. Therefore, this review aims to discuss applications of artificial intelligence in endoscopy, colonoscopy, and endoscopic ultrasound.
Keyphrases
- artificial intelligence
- deep learning
- ultrasound guided
- machine learning
- neural network
- big data
- healthcare
- magnetic resonance imaging
- risk factors
- randomized controlled trial
- convolutional neural network
- cardiovascular events
- physical activity
- type diabetes
- metabolic syndrome
- adipose tissue
- cardiovascular disease
- endoscopic submucosal dissection
- social media
- health insurance
- glycemic control