Predicting and managing chronic diseases using mobile health and artificial intelligence

Background and Aims: Chronic illnesses like diabetes and heart disease are piling pressure on healthcare worldwide, and it’s a real challenge to keep up. I’ve been digging into how mobile health tools like apps and wearables combined with artificial intelligence might help us predict and manage these conditions better. The goal here is to figure out if these tech-driven approaches actually make a difference for patients, and I’m betting they could outshine the usual methods. Methods: I scoured databases like PubMed, IEEE Xplore, and Scopus for studies from the last decade, up to ۲۰۲۵, focusing on adults with chronic conditions. I picked ۳۲ solid papers, covering ۱۵,۷۸۰ people, where researchers tested things like smartwatches or phone apps paired with AI tricks, such as machine learning. I looked at how they set up their studies, what gear they used, and what happened clinically, double-checking quality with the Cochrane Risk of Bias tool. Results: The results were pretty eye-opening. These mHealth-AI combos nailed disease predictions with an average accuracy score of ۰.۸۷, and they cut hospital readmissions by ۲۳%. For folks with diabetes, blood sugar levels dropped by nearly a point on the HbA۱c scale. Wearables with AI seemed to shine brightest for real-time tracking, though people in rural areas struggled to get on board mostly because of spotty internet. Conclusion: It’s clear this tech duo has serious potential to shake up how we handle chronic diseases, offering tailored care and catching problems early. But it’s not all smooth sailing we need solutions that reach everyone, especially in remote spots. I’d love to see more long-term studies and some number crunching on costs to really prove this can work day-to-day in clinics. It’s an exciting step toward smarter healthcare.

کلیدواژه ها:

Mobile Health ، Artificial Intelligence ، Chronic Disease