This paper is in the following e-collection/theme issue:

Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (423) Mobile Health (mhealth) (3519) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (217) Pharmacovigilance (174) Pharmacology and Pharmaceutics (118) Usability of Apps and User Perceptions of mHealth (1204)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65927, first published .
Investigating the Quality of Mobile Apps for Drug-Drug Interaction Management Using the Mobile App Rating Scale and K-Means Clustering: Systematic Search of App Stores

Investigating the Quality of Mobile Apps for Drug-Drug Interaction Management Using the Mobile App Rating Scale and K-Means Clustering: Systematic Search of App Stores

Investigating the Quality of Mobile Apps for Drug-Drug Interaction Management Using the Mobile App Rating Scale and K-Means Clustering: Systematic Search of App Stores

Authors of this article:

Ayush Bhattacharya1 Author Orcid Image ;   Jose Fernando Florez-Arango1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Bhattacharya A, Florez-Arango J. Cluster-Based Predictive Modeling of User Ratings for Physical Activity Apps Using Mobile App Rating Scale (MARS) Dimensions: Model Development and Validation. JMIR mHealth and uHealth 2025;13:e70987 View