Machine learning in precision diabetes care and cardiovascular risk prediction
EK Oikonomou, R Khera - Cardiovascular Diabetology, 2023 - Springer
Artificial intelligence and machine learning are driving a paradigm shift in medicine,
promising data-driven, personalized solutions for managing diabetes and the excess …
promising data-driven, personalized solutions for managing diabetes and the excess …
[HTML][HTML] Machine learning application in autoimmune diseases: State of art and future prospectives
MG Danieli, S Brunetto, L Gammeri, D Palmeri… - Autoimmunity …, 2024 - Elsevier
Autoimmune diseases are a group of disorders resulting from an alteration of immune
tolerance, characterized by the formation of autoantibodies and the consequent …
tolerance, characterized by the formation of autoantibodies and the consequent …
Basal-bolus advisor for type 1 diabetes (T1D) patients using multi-agent reinforcement learning (RL) methodology
This study presents in-silico design and verification of an advanced multi-agent
reinforcement learning (RL) strategy for personalized glucose regulation in individuals …
reinforcement learning (RL) strategy for personalized glucose regulation in individuals …
[HTML][HTML] A Self-Attention Deep Neural Network Regressor for real time blood glucose estimation in paediatric population using physiological signals
With the advent of modern digital technology, the physiological signals (such as
electrocardiogram) are being acquired from portable wearable devices which are being …
electrocardiogram) are being acquired from portable wearable devices which are being …
Spectrogram-Driven Convolutional Neural Network for Real-Time Non-invasive Hyperglycaemia Detection in Paediatric Type-1 Diabetes via Wearable Sensors
Real-time detection of glycaemic events is crucial in the effective management of type 1
diabetes, particularly in paediatric patients. Recent advances in wearable sensors and …
diabetes, particularly in paediatric patients. Recent advances in wearable sensors and …