International Journal of Artificial Intelligence in Medical Issues

Journal title	International Journal of Artificial Intelligence in Medical Issues
Initials	IJAIMI
Frequency	Two issues per year [May and November ]
DOI	Prefix 10.56705
Online ISSN	3025-4167
Editor-in-chief	Huzain Azis
Publisher	Yocto Brain
Accepatance Rate	-
Cite IJAIMI	.BIBTEX \| .RIS

The International Journal of Artificial Intelligence in Medical Issue (IJAIMI) is a premier, peer-reviewed academic journal dedicated to the integration and advancement of artificial intelligence (AI) in the medical field. The journal aims to serve as a global platform for researchers, clinicians, engineers, and other professionals to share their findings, methodologies, and innovations related to AI's application in medical diagnostics, treatment, patient care, and health systems.

Key Topics:

AI-powered diagnostic tools and imaging
Predictive modeling in patient care
Machine learning applications in genomics and personalized medicine
Robotics and automation in surgery and rehabilitation
Natural language processing for medical records and patient communication
Ethical considerations and implications of AI in medicine
Integration of AI in telemedicine and remote patient monitoring
Deep learning in drug discovery and pharmaceutical research
Neural networks in epidemiology and disease outbreak prediction
AI-driven health informatics and data analytics

Publication Frequency:

IJAIMI is issued twice a year, with editions releasing in May and November, focusing on emerging trends, transformative research, and paradigm shifts at the intersection of AI and medical sciences.

Current Issue

Vol. 4 No. 1 (2026): International Journal of Artificial Intelligence in Medical Issues

The articles in this issue (7 Original Articles) were authored or co-authored by 24 unique authors from one country, Indonesia, and represented 19 affiliations: Universitas Almarisah Madani; Politeknik Negeri Batam; Universitas Palangka Raya; Politeknik Negeri Kupang; Universitas Islam Negeri Raden Intan Lampung; Politeknik Negeri Jember; Universitas Islam Sultan Agung Semarang; Universitas Megarezky; STIMIK El Rahma Yogyakarta; Universitas Trilogi; Politeknik Negeri Banjarmasin; Universitas Bina Darma; Universitas Sembilanbelas November Kolaka; Universitas Teknologi Yogyakarta; Institut Bisnis dan Teknologi Indonesia; Universitas Teknologi Digital Indonesia; Universitas Ahmad Dahlan; Institut Teknologi dan Bisnis STIKOM Ambon; and Universitas Jenderal Achmad Yani Yogyakarta.

DOI: https://doi.org/10.56705/61zeaf69

Published: 2026-05-30

Articles

Explainable Machine Learning for Predicting the Mental Health Impact of AI and Digital Platform Usage among Students

Agus Halid, Dwi Amalia Purnamasari, Ade Chandra Saputra, Nicodemus Mardanus Setiohardjo

1-18
- PDF
Leakage-Aware and Explainable Machine Learning for Healthcare Claim Fraud Detection Using Imbalanced Medical Insurance Data

Dian Hafidh Zulfikar, Ery Setiyawan Jullev Atmadji, Bagus Satrio Wahyu Poetro

19-34
- PDF
Confidence-Aware Depression Severity Detection in Low-Resource Urdu Social Media Text: A Multilingual Machine Learning Approach

Ahmad Naswin, Yuli Praptomo Pamungkas Hari Sungkowo

35-53
- PDF
Depression Risk Prediction Among Teenagers Using Explainable Machine Learning and Imbalanced Behavioral Data

Rudi Setiawan, Effan Najwaini, Rezania Agramanisti Azdy, Rasmiati Rasyid

54-71
- PDF
Machine Learning-Based Clustering of Viruses Using Taxonomic and Genomic Features for Health Informatics Applications

Adityo Permana Wibowo, Made Leo Radhitya, Edi Faizal, Ika Arfiani

72-92
- PDF
A Comparative Study of Machine Learning Models for Stress Level Classification Using Social Media and Lifestyle Data

M. Ikbal Siami, Aris Wahyu Murdiyanto, Sumiyatun

93-109
- PDF
Gender-Aware Prediction of Liver Disease Using Machine Learning and Clinical Laboratory Data

Umar Zaky, Muhammad Habibi, Adri Priadana, Thomas Edyson Tarigan

110-130
- PDF

View All Issues

International Journal of Artificial Intelligence in Medical Issues

Current Issue

Articles

Explainable Machine Learning for Predicting the Mental Health Impact of AI and Digital Platform Usage among Students

Leakage-Aware and Explainable Machine Learning for Healthcare Claim Fraud Detection Using Imbalanced Medical Insurance Data

Confidence-Aware Depression Severity Detection in Low-Resource Urdu Social Media Text: A Multilingual Machine Learning Approach

Depression Risk Prediction Among Teenagers Using Explainable Machine Learning and Imbalanced Behavioral Data

Machine Learning-Based Clustering of Viruses Using Taxonomic and Genomic Features for Health Informatics Applications

A Comparative Study of Machine Learning Models for Stress Level Classification Using Social Media and Lifestyle Data

Gender-Aware Prediction of Liver Disease Using Machine Learning and Clinical Laboratory Data

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