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

Clinical Information and Decision Making (3717) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (984) Decision Support for Health Professionals (2244) Cardiac Risk and Cardiac Risk Calculators (174) Artificial Intelligence (4798)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73131, first published .
Young Asian nurse with stethoscope and backpack in lush green terraced fields.

AI-Assisted Cardiovascular Risk Assessment by General Practitioners in Resource-Constrained Indonesian Settings Using a Conceptual Prototype: Randomized Controlled Study

AI-Assisted Cardiovascular Risk Assessment by General Practitioners in Resource-Constrained Indonesian Settings Using a Conceptual Prototype: Randomized Controlled Study

Authors of this article:

Anindya Pradipta Susanto1, 2, 3 Author Orcid Image ;   David Lyell1 Author Orcid Image ;   Bambang Widyantoro4 Author Orcid Image ;   Dafsah Arifa Juzar4 Author Orcid Image ;   Anwar Santoso4 Author Orcid Image ;   Shlomo Berkovsky1 Author Orcid Image ;   Farah Magrabi1 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Susanto A, Lyell D, Widyantoro B, Berkovsky S, Magrabi F. Designing AI tools to advance health equity in resource-constrained low- and middle-income countries. DIGITAL HEALTH 2026;12 View
  2. Leon Altamirano C, Manuel Correa F. Analysis of the Acceptability of Telemedicine in patients with Diabetes Mellitus. SAP Primary Care 2025;1:24 View
  3. Muhammad Furqan Nazuli , Rudiansyah , Muhammad Hanif . Pengembangan Sistem Triase IGD Berbasis <i>Web</i> dengan <i>Decision Tree </i>dan Notifikasi <i>Real-Time</i>. BETRIK 2026;17(02):301 View