The Impact of Foundational Models on Patient-Centric e-Health Systems

--As Artificial Intelligence (AI) becomes increasingly embedded in healthcare technologies, understanding the maturity of AI in patient -centric applications is critical for evaluating its trustworthiness, transparency, and real -world impact. In this study, we investigate the integration and maturity of AI feature integration in 116 patient-centric healthcare applications. Using Large Language Models (LLMs), we extracted key functional features, which are then categorized into different stages of the Gartner AI maturity model. Our results show that over 86.21% of applications remain at the early stages of AI integration, while only 13.79% demonstrate advanced AI integration. Artificial Intelligence (AI) is rapidly gaining traction across various sectors, including health care. However, the current state and maturity of its integration into real -world mobile health applications remain largely underexplored. In particular, it is not yet clear who the primary users of these AI - enabled features are, patients or health care providers, and for what specific purposes they are being employed. Foundational Models (FMs), large-scale AI models trained on diverse and extensive datasets, have recently emerged as a transformative force across multiple domains.