Machine Learning Methods to Predict Diabetes Complications

By A. Dagliati, Simone Marini, L. Sacchi, Giulia Cogni, M. Teliti, V. Tibollo, Pasquale De Cata, Luca Chiovato, Riccardo Bellazzi. Journal of Diabetes Science and Technology, 2018

350 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Information Management, Information Systems

View Paper: https://www.semanticscholar.org/paper/d836a8d6a0ec72fe1564c30a5fabce2463e79188

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Josep Vehí
2. Iván Contreras

Citations in the corpus

• Artificial Intelligence for Diabetes Management and Decision Support: Literature Review (2018, background): “The MOSAIC project [100,110,112,128], another important project, is focused on the development of a DSS for T2D management, with a special focus on the risk assessment of related complications using data mining methods.”