Explainable Artificial Intelligence in Healthcare

Shih Chih Chen (Department of Information Management, National Kaohsiung University of Science and Technology, Taiwan)

Explainable Artificial Intelligence in Healthcare (XAIH) is an international, peer-reviewed scholarly journal dedicated to advancing research and innovation in explainable artificial intelligence (XAI) and its applications in healthcare and medical systems. It publishes high-quality research articles, reviews, and case studies that explore transparent, interpretable, and trustworthy AI models designed to support healthcare decision-making, clinical practice, and patient-centered care. The journal serves as a global platform for researchers, healthcare professionals, policymakers, and technologists to exchange knowledge and address the challenges of implementing ethical and accountable AI in healthcare environments.

Topics covered include:

Explainable AI Models for Clinical Decision Support; Interpretable Machine Learning in Medical Diagnosis and Prediction; Transparent AI Systems for Medical Imaging and Healthcare Analytics; Ethical, Trustworthy, and Responsible AI in Healthcare; Human-Centered AI and Physician–AI Collaboration; AI Fairness, Bias Detection, and Accountability in Medical Systems; AI-Driven Personalized Medicine and Precision Healthcare; Regulatory, Legal, and Governance Frameworks for Explainable Healthcare AI.

XAIH aims to foster interdisciplinary collaboration among experts in artificial intelligence, medicine, health informatics, data science, bioengineering, and healthcare policy. The journal contributes to the advancement of transparent and reliable AI technologies that improve healthcare quality, patient safety, and clinical trust. Papers published in XAIH are grounded in rigorous theoretical, empirical, or applied research and are expected to clearly articulate their contributions to both scientific understanding and healthcare practice. Authors are encouraged to develop innovative explainability approaches while addressing broader implications such as ethics, privacy, accountability, and inclusivity in healthcare systems. In alignment with global priorities, XAIH welcomes research that supports sustainable healthcare innovation and contributes to the achievement of the United Nations 2030 Sustainable Development Goals (SDGs).

Subject Area and Category:

Explainable Artificial Intelligence in Healthcare focuses on the development, evaluation, and implementation of interpretable AI technologies in healthcare systems. The journal covers research on Explainable Machine Learning Models; Clinical Decision Support Systems; Transparent Medical Imaging Analytics; Ethical and Trustworthy AI in Healthcare; Personalized and Precision Medicine; AI Fairness and Accountability; and Healthcare Data Analytics and Governance. It also addresses interdisciplinary and real-world applications across hospitals, public health systems, digital health platforms, biomedical research, and healthcare policy environments.

Starting publishing date: 2025

Frequency: Quarterly (February, May, August, and November)

Indexed on: