JMIR Publications

ABSTRACT

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health applications (mHealth apps) could considerably assist both individuals and healthcare professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable and effective mHealth apps. Here we review the rationale and guidelines for implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of non-communicable diseases. We suggest that a co-creation-based framework is the best method for tackling these challenges. Finally, we describe the current and future role of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote healthcare will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack both of standardized methods to measure the clinical outcomes of mHealth apps and of techniques to encourage user engagement and behavior change in the long term. We expect that in the near future, these obstacles will be overcome and that the on-going European project WARIFA will provide significant advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.