Aims and Scope
The journal focuses on work that sits at the intersection of clinical practice and artificial intelligence. Our aim is to highlight research that doesn’t just explore AI from a theoretical angle, but shows how these tools behave in real clinics, hospitals, and community health environments. We’re interested in studies that move the conversation forward — even if the results are imperfect — as long as they offer something meaningful for clinicians and researchers trying to understand how AI can fit into everyday care.
The scope is intentionally broad because AI touches so many parts of medicine. We look for research that tests new ideas, challenges assumptions, or explains practical problems others might face. Whether the work comes from a large hospital system, a small clinical team, or a research lab, what matters most is that it adds clarity to the real-world use of AI in health.
| Category | Scope Areas Included |
|---|---|
| Clinical Applications of AI | Diagnostic support, treatment planning, triage systems, disease risk prediction, AI in radiology, pathology, dermatology, cardiology, oncology, and other specialties |
| Model Development & Validation | Machine learning models, deep learning pipelines, model performance assessment, bias detection, generalizability studies, dataset curation |
| AI in Healthcare Operations | Workflow optimization, resource planning, patient flow prediction, automation of clinical tasks, documentation tools |
| Decision Support & Safety | Clinical decision support tools, risk alerts, early warning systems, safety monitoring, human–AI collaboration in care |
| Ethics, Governance & Policy | Responsible AI, fairness, transparency, explainability, regulatory issues, clinical implementation barriers |
| Digital Health & Data Science | Wearables, remote monitoring, EHR analytics, natural language processing, multimodal data integration |
| Education & Training | AI literacy for clinicians, curriculum development, simulation-based training, competency frameworks |
| Case Studies & Real-World Evaluations | Implementation studies, pilot programs, quality-improvement experiences, post-deployment performance of AI tools |
| Reviews & Perspectives | Systematic reviews, scoping reviews, expert viewpoints, methodological discussions |
