Artificial intelligence in mobile health applications: A comprehensive review of its role in diabetes care

Table 1 Comparison of artificial intelligence applications in diabetes care

AI application area	Primary AI techniques used	Key benefits
Predictive analytics	Machine learning, ensemble models	Early diabetes prediction and prevention
Continuous glucose monitoring	Recurrent neural networks, LSTM	Real-time glycemic control and hypoglycemia prevention
Personalized self-management	Reinforcement learning, behavioral AI	Tailored interventions based on patient data
Early risk assessment	Deep learning, NLP	Such as diabetic retinopathy and neuropathy
Clinical decision support	Rule-based systems, reinforcement learning	Optimized treatment plans and reduced clinician burden

AI: Artificial intelligence; LSTM: Long short-term memory; NLP: Natural language processing.