| Summary: | The recent healthcare transformations emphasize the importance of individuals maintaining a healthy lifestyle through proper nutrition and physical activity to reduce the risk of severe illnesses. Patients often search for information on their own, leading to uncertainty about appropriate diets or fitness activities. Consequently, many individuals cross-check information or health advice from various sources. However, some people hesitate to verify online health-related information with their clinicians, fearing that it may be perceived as a challenge to their expertise and authority. This study aimed to determine a useful way to monitor a patient’s lipid profile and provide recommendations for meal plans and fitness activities. A content-based approach that utilizes a vector space model is employed in the development of a recommender method. The vector space model uses meal plan keywords to suggest similar items, and selection rules are applied to identify relevant meal plan and fitness activity options. This approach has been integrated into a mobile application for healthcare, enabling patients to receive personalized recommendations based on their lipid levels. To assess the usability of the mobile application, an initial user study was conducted, which revealed that most respondents had a positive opinion of the application. In the future, the application could be enhanced with a wider variety of meal plans and additional features. © 2024 by the authors of this article.
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