The Use of Machine Learning Approaches in Clinical Research of Diabetes

Machine learning is a subset of AI where computer models are trained to learn from their actions and environment over time, with the intention of performing better. Machine learning is increasingly applied to clinical areas, particularly diabetes. Machine learning approaches have the potential to improve risk stratification and outcome prediction within many clinical applications. Novel solutions to problems developed through machine learning are themselves leading to questions of morality and ethics.

The goal of this research topic is to present best practice use of AI and machine learning in the clinical research of diabetes, showcase the use of big data to develop intelligent systems, and highlight the ethical implications of such technologies.

Specific themes of interest include, but are not limited to:
- Uses of machine learning and AI in the clinical research of diabetes
- The use of big data to develop patient-centred care for diabetes
- The ethical implications of machine learning approaches in the clinical research of diabetes

All manuscripts accepted by Frontiers are encouraged.







Declaration: Arjun Panesar is the Founder of DDM Health which Petra collaborates with.