Explainable Artificial Intelligence in Healthcare
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.
Aims and Scope
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.