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Review analyzes effectiveness and trends of AI in mobile health, highlighting its impact on chronic disease and personalized support.
The integration of artificial intelligence (AI) with mobile health (mHealth) applications has transformed the healthcare landscape by offering early disease detection, accessible, real-time, and personalized medical support. This review examines the current state and trends of AI-powered mobile health applications, examining their implementation across various medical domains such as mental health, chronic disease management, visual impairment, stroke rehabilitation, and fitness. A comprehensive analysis of peer-reviewed literature from 2015 to 2025 was conducted, focusing on the types of AI algorithms used, their target applications, and overall effectiveness. The findings reveal an increasing trend in scholarly interest, particularly in journal publications, reflecting the demand for validated and reliable AI health solutions. Neural networks and deep learning models dominate the algorithmic landscape due to their effectiveness in handling complex and unstructured health data. This study highlights the growing reception and potential of AI-integrated mHealth apps to revolutionize personal healthcare and surface the way for more intelligent, user-centric solutions.
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Salihu et al. (2025) studied this question.
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