Digital Health and Clinical Intelligence is an international, peer-reviewed, open access journal dedicated to publishing high-quality research on digital health, clinical artificial intelligence, medical informatics, and intelligent healthcare systems. The journal provides a scholarly platform for research that advances the safe, effective, ethical, and evidence-based use of digital technologies in healthcare delivery, clinical practice, public health, and health-system management.
The journal welcomes original research articles, review papers, clinical validation studies, implementation reports, methodological studies, case studies, and policy-oriented contributions. It encourages interdisciplinary work that connects medicine, computer science, data science, biomedical engineering, public health, health informatics, and healthcare policy.
With a strong focus on clinical relevance and real-world impact, the journal aims to support innovation that improves diagnosis, treatment, monitoring, patient care, health equity, and system performance. It serves clinicians, researchers, health informaticians, AI scientists, public health professionals, policymakers, healthcare administrators, and digital health innovators working to transform healthcare through responsible digital and intelligent technologies.
Aims & Scope
Digital Health and Clinical Intelligence aims to advance research and innovation in digital health, clinical AI, medical informatics, and intelligent healthcare systems. The journal welcomes theoretical, empirical, experimental, computational, clinical, implementation, and policy-relevant studies that contribute to safer, smarter, and more equitable healthcare.
Areas of Interest
- Digital health technologies and healthcare innovation
- Clinical artificial intelligence and healthcare AI applications
- Clinical decision-support systems
- Medical informatics, health information systems, and healthcare data systems
- Electronic health records and clinical data analytics
- Digital diagnostics and predictive healthcare
- AI-assisted diagnosis, prognosis, and treatment planning
- Medical imaging systems, computer vision, radiomics, and image analysis
- Telemedicine, telehealth, virtual care, and remote consultation
- Mobile health, connected health, and Internet of Medical Things
- Wearable devices and remote patient monitoring
- Biomedical sensors, biosensing technologies, and biomedical instrumentation
- Medical technology, medical devices, and point-of-care technologies
- Diagnostics and monitoring technologies
- Personalized medicine and precision health
- Digital therapeutics and technology-enabled care models
- Public health intelligence and digital epidemiology
- Health engineering and healthcare systems engineering
- Hospital technology systems and smart healthcare infrastructure
- Healthcare automation and intelligent systems
- Rehabilitation engineering and assistive technologies
- Allied health technologies and clinical support innovation
- Human-centered design, usability, human factors engineering, and patient engagement
- Patient safety, clinical workflow, and quality improvement
- Explainable, trustworthy, and responsible AI in healthcare
- Ethics, privacy, security, and governance of health data
- Health equity, access, and digital inclusion
- Clinical validation, translational research, implementation, and evaluation of digital health tools
- Regulation, policy, and standards for digital health and clinical AI