CALL FOR PAPERS - AI Enabled Telehealth and Virtual Care
THMT is an internationally indexed, peer reviewed journal dedicated to publishing high quality research that delivers measurable digital health outcomes and real world impact for academia, healthcare systems, and industry. Editors invite
high value original submissions that advance the science, policy, or practical delivery of AI enabled telehealth and virtual care, including:
Clinical Applications
- Generative AI in clinical workflows, documentation, triage, and decision support
- AI-enhanced specialty telehealth: mental health,
dermatology, radiology, pathology, stroke, cardiology, critical care
- Virtual surgical planning, robotic telepresence, and remote surgical assistance
- Chronic disease management and personalized care platforms
- Pediatric and geriatric virtual care adaptations
Remote Monitoring & Diagnostics
- Remote monitoring, predictive analytics, digital diagnostics, and virtual wards
- IoT, wearables, and technology-assisted home care
- Voice biomarkers, ambient sensing, and passive monitoring
- Digital phenotyping and behavioral pattern recognition
- Multi-modal AI fusion (imaging, wearables, EHR, patient reported outcomes)
Patient-Facing Technologies
- Conversational AI and virtual health assistants
- AI-powered patient education and health literacy tools
- Natural language processing for multilingual telehealth and accessibility
- Medication adherence monitoring and intervention
- Virtual and augmented reality in telehealth
Data Science & Infrastructure
- Real-time risk stratification, early warning systems, and population health analytics
- Federated learning and privacy-preserving AI
- Interoperability, cloud infrastructure, edge computing, and 5G enablement
- Time-series analysis and longitudinal patient modeling
- Social determinants of health modeling in virtual care
Regulation, Ethics & Governance
- Regulation, ethics, data governance, cybersecurity, and medico-legal issues
- Algorithmic bias, fairness, equity, and transparency (XAI)
- Reimbursement models and value-based care frameworks
Implementation & Evaluation
- Implementation science, health economics, and workforce transformation
- Clinician-AI collaboration and human-in-the-loop design
- Patient trust, engagement, and digital equity
- Clinician burnout mitigation through AI workflow optimization
Validation & Quality
- Clinical
validation frameworks for AI diagnostic and prognostic tools
- Algorithm drift detection and model recalibration
- Safety monitoring and adverse event reporting
- Comparative effectiveness research
Emerging Applications
- AI in pandemic response and infectious disease surveillance
- Precision medicine and genomic integration
- Hospital-at-home programs and decentralized clinical trials
- Remote rehabilitation with computer vision and motion analysis
- Pharmacovigilance and environmental health monitoring
What We're Looking For
Your organization is producing real world evidence on telehealth outcomes, cost efficiency, and implementation success. We publish measurable results that healthcare executives and policymakers actually
use.
We welcome: Implementation case studies • ROI analyses • Pilot results • Validation studies • Technical innovations • Policy analyses • Comparative effectiveness research
Article Types & Limitations: Original Research • Systematic Reviews & Meta-Analyses • Technical/Innovation Reports • Case Studies • Policy/Regulatory
Analyses • Perspectives & Commentaries • Short Communications • Letters
Word limit: 8,000 words including references
Manuscript Preparation & Submission
Preparation guidelines:
https://telehealthandmedicinetoday.com/index.php/journal/manuscriptprep
Submission portal:
https://telehealthandmedicinetoday.com/index.php/journal/about/submissions
THMT encourages open data, code sharing, and supplementary materials.
APC Fee Model
- No fee for failed/negative experiments or editorials
Deadline: Rolling submissions
Contact: info@partnersindigitalhealth.com
Learn more: https://telehealthandmedicinetoday.com/index.php/journal/THMT
