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

Clinical Informatics (1309) Machine Learning (2051) Hypertension Prevention and Treatment (294) Artificial Intelligence (2089) Cardiology (219) Cardiac Disease Management (152) Applications of AI (275) Clinical Information and Decision Making (1893)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54357, first published .
Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning–Based Multicohort (RIGIPREV) Study

Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning–Based Multicohort (RIGIPREV) Study

Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning–Based Multicohort (RIGIPREV) Study

Authors of this article:

Iván Cavero-Redondo1, 2 Author Orcid Image ;   Arturo Martinez-Rodrigo3 Author Orcid Image ;   Alicia Saz-Lara1 Author Orcid Image ;   Nerea Moreno-Herraiz1 Author Orcid Image ;   Veronica Casado-Vicente4, 5 Author Orcid Image ;   Leticia Gomez-Sanchez6 Author Orcid Image ;   Luis Garcia-Ortiz7, 8, 9 Author Orcid Image ;   Manuel A Gomez-Marcos7, 8, 10 Author Orcid Image ;   RIGIPREV Investigators Group1, 7, 11
Article Authors Cited by (5) Tweetations (1) Metrics

Journals

  1. Mohana Priya A, Rajesh Kanna P, Vanithamani S, Sathish Kumar G. An efficient optimized deep learning model for the risk prediction of arterial stiffness in diabetes patients. Biomedical Signal Processing and Control 2025;110:108161 View
  2. Liu K, Lin Z, Chen Y, Hong H. Elevated pulse wave velocity as a marker of arterial stiffness and its association with mortality in US adults. Scientific Reports 2025;15(1) View
  3. Ben-Aicha S, Srivastava P, Kararigas G, Devaux Y, Emanueli C, Sopic M. Harnessing multiomics technologies and machine learning for advancing personalized theranostic approaches in atherosclerosis. Pharmacological Reviews 2025;77(6):100091 View
  4. Leng J, Zhang Y, Hu F, Zhang M, Ho P. FEMTL-DR: A feature-enhanced multi-task learning model for flexible drug recommendation. Neurocomputing 2026;659:131806 View
  5. Ri J, Jo K, Mun T. Simulating a Specialist's Treatment Experience for Hypertension Using Deep Neural Networks. The Journal of Clinical Hypertension 2025;27(10) View