A systematic review on eHealth technology personalization approaches.

ABSTRACT: Despite the widespread use of personalization of eHealth technologies, there is a lack of comprehensive understanding regarding its application. This systematic review aims to bridge this gap by identifying and clustering different personalization approaches based on the type of variables used for user segmentation and the adaptations to the eHealth technology and examining the role of computational methods in the literature. From the 412 included reports, we identified 13 clusters of personalization approaches, such as behavior + channeling and environment + recommendations. Within these clusters, 10 computational methods were utilized to match segments with technology adaptations, such as classification-based methods and reinforcement learning. Several gaps were identified in the literat

SUBMITTER: Klooster IT 

PROVIDER: S-EPMC11406103 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature