About the Journal

International Journal of Artificial Intelligence in Health and Medicine is an open-access, peer-reviewed scholarly journal that publishes high-quality research at the intersection of artificial intelligence (AI) and healthcare. The journal serves as a global platform for researchers, clinicians, policymakers, and technologists to share scientific advancements, innovative methodologies, and evidence-based applications of AI in medicine.

International Journal of Artificial Intelligence in Health and Medicine welcomes original contributions that explore how AI technologies can improve patient outcomes, optimize healthcare processes, enhance diagnostics, and support clinical decision-making. The journal also addresses the ethical, legal, and societal implications of AI in the medical field.

Scope

Topics of interest include, but are not limited to:

  • Medical Imaging and Diagnostics: AI methods for MRI, CT, ultrasound, and other imaging modalities.

  • Predictive Analytics: Models for disease prognosis, patient outcomes, and treatment response prediction.

  • Personalized Medicine: AI-driven approaches tailored to individual genetic, environmental, and lifestyle factors.

  • Electronic Health Records (EHRs): Data mining, natural language processing, and trend analysis.

  • Telemedicine and Remote Monitoring: AI-powered systems for remote patient care.

  • Robotics in Medicine: Surgical assistance, rehabilitation, and clinical automation.

  • Ethics, Policy, and Regulation: Responsible and transparent AI adoption in healthcare.

Publication Model

  • Frequency: 2 Years

  • Access: Open access – all articles are freely available without subscription fees.

  • Peer Review: Double-blind peer review to ensure impartiality and academic rigor.

  • Language: English (abstracts may be available in additional languages).

Mission Statement

The mission of International Journal of Artificial Intelligence in Health and Medicine is to advance scientific understanding and practical implementation of artificial intelligence in healthcare, fostering interdisciplinary collaboration to deliver impactful, ethical, and sustainable innovations that benefit global health.

Current Issue

Articles

Comparative Analysis of Machine Learning Models for Heart Disease Classification: Evaluation of Random Forest, XGBoost, and Logistic Regression with Hyperparameter Optimization

Tomás López Aníbal (University of Otago, New Zealand)
Lai li-We (National Cheng Kung University, Taiwan, Province of China)
Abstract View : 9     PDF downloads: 1
1-11

PDF

Hybrid Deep Learning Architecture with Interpretable Feature Selection for Breast Cancer Diagnosis from Fine Needle Aspirate Images

Rabiu Okanlawon (University of Ghanaiversity of Pretoria, Ghana)
K Castaño (Universidad Tecnológica de Pereira, Colombia)
Abstract View : 7     PDF downloads: 2
12-18

PDF

Explainable AI-Based Heart Disease Classification: A Deep Learning Framework with Limited Features and Clinical Interpretability for Resource-Constrained Healthcare Settings

Jaminton Muñoz (Universidad Tecnológica de Pereira, Colombia)
Giannis Tzoulis (University of Patras, Greece)
Abstract View : 7     PDF downloads: 2
19-28

PDF

Hybrid Ensemble Learning with Active Feature Selection for Early-Stage Cardiovascular Risk Stratification: A Multi-Modal Approach Using UCI Clinical Biomarkers

Panom Tamene (Hawassa University, Ethiopia)
Koundé Moanu (Université Paris-Saclay, France)
Abstract View : 14     PDF downloads: 7
29-35

PDF

Federated Learning-Based Heart Disease Prediction with Privacy-Preserving Clinical Data Fusion: A Comparative Analysis of Lightweight AI Models for Distributed Healthcare Systems

Amit Vijayan (Birla Institute of Technology and Science, India)
Abstract View : 10     PDF downloads: 2
36-42

PDF

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