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All Journal International Journal of Advances in Applied Sciences JUITA : Jurnal Informatika JURNAL PENGABDIAN KEPADA MASYARAKAT JURNAL MANAJEMEN DAN PELAYANAN FARMASI (Journal of Management and Pharmacy Practice) Prosiding Seminar Nasional Program Pengabdian Masyarakat JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit)
Merita Arini
Universitas Muhammadiyah Yogyakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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Mapping artificial intelligence applications in electronic medical records research Bima Ananta Putra; Merita Arini
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp646-655

Abstract

The integration of electronic medical records (EMR) and artificial intelligence (AI) in healthcare improves data accessibility, security, diagnostic accuracy, personalized care, and overall system performance. Despite increasing interest, a comprehensive understanding of the field’s development, key contributions, and dominant research themes remains limited. This study presents a bibliometric analysis of 681 articles selected from 1893 initial records retrieved from the Scopus database (2015–2025) using the keywords “electronic medical record” AND “artificial intelligence.” Data were analyzed using Microsoft Excel for trend analysis and VOSviewer for keyword co-occurrence and thematic clustering. Results show steady publication growth, mainly from developed countries and health informatics institutions. Four main research themes emerged: i) AI adoption in healthcare systems, ii) patient characteristics and clinical assessment, iii) predictive models and machine learning (ML) algorithms, and iv) deep learning (DL) and diagnostic accuracy. Nevertheless, research gaps persist in areas such as patient safety, data privacy, ethical issues, primary care implementation, healthcare workforce roles, and specific algorithmic approaches. Trust in AI systems also requires deeper investigation.
Co-Authors Amelia Inggamal Anisa Dwijayanti Arfan Ramadhana Arlina Dewi Azzahra Nabila Bima Ananta Putra Cornel Anggara Dirwan Suryo Soularto Ekorini Listiowati Ekorini Listiowati, Ekorini Ekorini Listyowati Farid Suryanto Firman Pribadi Harumi Iring Primastuti Ikrima Khaerun Nisa Imam Riadi Irvan Adji Satriawan Junior Hendri Wijaya Mohammad Agus Samsudin Muhammad Ahtareja Faqih Nabila Setyoningsih Nur Hikmah Pratiwi Nuryakin, Nuryakin Sasabila Zahraputri Arwani Yurni Dwi Astuti