Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.
Ivan ContrerasJosep VehíPublished in: Journal of medical Internet research (2018)
We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life.
Keyphrases
- artificial intelligence
- machine learning
- type diabetes
- big data
- deep learning
- cardiovascular disease
- glycemic control
- end stage renal disease
- ejection fraction
- healthcare
- chronic kidney disease
- newly diagnosed
- primary care
- peritoneal dialysis
- case report
- prognostic factors
- physical activity
- risk factors
- adipose tissue
- weight loss
- patient reported outcomes
- quality improvement