The Journal of Artificial Intelligence for Healthcare Systems (JAIHS), [ISSN: 3149-8981], published by Clinical Intelligence Research Press, is an international, peer-reviewed journal dedicated to research at the intersection of artificial intelligence, medicine, and healthcare systems. The journal provides a platform for researchers, clinicians, engineers, data scientists, health informaticians, and healthcare professionals to publish original and evidence-based contributions concerning the development, evaluation, implementation, and responsible use of intelligent technologies in healthcare.
JAIHS publishes original research articles, review articles, systematic reviews, methodological papers, technical studies, and interdisciplinary contributions. The journal covers theoretical advances, computational methods, clinical evaluation, healthcare implementation, and real-world applications of artificial intelligence.
The journal’s scope includes:
Artificial Intelligence in Healthcare, including AI-assisted diagnosis, prognosis, treatment planning, clinical risk assessment, and patient care
Machine Learning and Deep Learning for clinical, biomedical, and healthcare applications
Clinical Decision Support Systems and Intelligent Medical Systems
Medical Imaging, Computer Vision, and image-based disease detection and assessment
Natural Language Processing for clinical notes, biomedical literature, patient records, and healthcare communication
Healthcare Informatics, clinical informatics, biomedical information processing, and healthcare information systems
Digital Health, connected health technologies, and AI-enabled healthcare delivery
Predictive Analytics, clinical forecasting, patient stratification, and outcome prediction
Healthcare Data Science, Clinical Data Mining, and Medical Data Analytics
Electronic Health Records, clinical data integration, interoperability, data quality, and privacy-preserving analytics
Telemedicine, remote patient monitoring, virtual care, and AI-supported remote healthcare services
Smart Healthcare Systems and intelligent hospital, clinical, and patient-monitoring environments
Explainable AI, including interpretable, transparent, reliable, and trustworthy healthcare AI
Ethical AI in Healthcare, including fairness, bias, accountability, privacy, governance, and regulatory considerations
Healthcare Management and Health System Optimization using AI, data analytics, and computational modelling
Precision Medicine, personalized treatment, biomarker analysis, and data-driven clinical decision-making
AI-Driven Diagnostics, including model development, clinical validation, diagnostic performance, and implementation
Internet of Medical Things (IoMT), including connected medical devices, wearable sensors, intelligent monitoring, and secure health-data exchange
The journal also welcomes research on the clinical validation, usability, safety, economic evaluation, implementation, and organizational impact of AI-based healthcare technologies. Studies addressing human–AI interaction, algorithmic bias, data security, regulatory compliance, and the ethical or social implications of artificial intelligence in healthcare are within scope.
Submissions must demonstrate a clear and substantial connection between artificial intelligence and healthcare or medical systems. Manuscripts focused solely on general computer science, standalone algorithm development, healthcare administration, or non-medical datasets without a meaningful healthcare application or evaluation are outside the journal’s scope.
Clinical Intelligence Research Press