Trustworthy, Human-Centered AI for Digital Health Data Ecosystems: Data Technologies, Governance, and Empirical Evaluation
DETAILS
Call for Papers
Trustworthy, Human-Centered AI for Digital Health Data Ecosystems: Data Technologies, Governance, and Empirical Evaluation
Journal: Data Technologies and Applications
Publisher: Emerald Publishing
Manuscript Submission Opens: 1 October 2026
Manuscript Submission Deadline: 30 June 2027
Data Technologies and Applications invites submissions for a Special Issue examining how trustworthy and human-centered artificial intelligence can be designed, governed, evaluated, and deployed across digital health data ecosystems.
About the Special Issue
Artificial intelligence is increasingly integrated into clinical decision support, medical imaging, clinical natural language processing, patient-facing chatbots, remote monitoring, precision medicine, public-health surveillance, and health-information management. Generative AI and foundation models are further expanding these applications through multimodal reasoning, clinical documentation, triage, record summarization, and knowledge discovery.
This Special Issue approaches health AI as a data-intensive socio-technical system, focusing on the technologies, information-management practices, governance mechanisms, human-AI interactions, and evaluation approaches needed for trustworthy adoption in real healthcare environments. Particular attention is given to human oversight, technical robustness, safety, privacy, transparency, fairness, accountability, and lifecycle monitoring.
Topics of Interest
Submissions may address, but are not limited to:
Data quality and provenance in AI-enabled healthcare
Bias, missingness, and representativeness in health data
Interoperability and linked health data
Semantic web and knowledge graphs for digital health
Standards for AI-enabled health data ecosystems
Explainable and transparent healthcare AI
Auditable AI for clinical and public-health decision-making
Human-centered AI in healthcare
Clinician-AI collaboration
AI integration into clinical workflows
User trust in healthcare AI systems
Patient-facing artificial intelligence
Health chatbots and generative AI assistants
Online health information behaviour
Clinical natural language processing
Large language models in healthcare
Multimodal AI models and their evaluation
Privacy-preserving health analytics
Federated learning
Secure health-data sharing
Health-data governance
Fairness, equity, and inclusion in health AI
Real-world evidence for AI systems
Post-deployment monitoring and model drift
Lifecycle governance for healthcare AI
AI-based recommendation and classification
Prediction and clinical decision-support systems
AI applications using electronic health records
Imaging, wearable, claims, and public-health data
Preferred Article Types
The Special Issue welcomes:
Full research articles
Systematic reviews
Short communications
Interdisciplinary contributions from computational research, information systems, information science, health informatics, social science, design science, and policy-oriented research are encouraged.
Research and Methodological Approaches
Submissions should include relevant empirical evidence, rigorous evaluation, or systematic review and may employ:
Machine-learning experiments
Benchmark evaluations
Human-subject studies
Surveys and interviews
Case studies
Longitudinal analyses
Digital-trace analysis
Bibliometric methods
Mixed-methods research
Research should move beyond proof-of-concept development and contribute toward trustworthy deployment in clinical, public-health, or patient-facing environments.
Submission Information
Submission Opens: 1 October 2026
Submission Deadline: 30 June 2027
Full manuscripts should be submitted through the Data Technologies and Applications ScholarOne Manuscripts system.
Authors must select “Trustworthy, Human-Centered AI for Digital Health Data Ecosystems: Data Technologies, Governance, and Empirical Evaluation” from the Special Issue options during submission.
Submitted manuscripts must follow the journal's author guidelines, be original, and must not have been previously published or be under consideration elsewhere while under review.
Guest Editors
Guipeng Lan
Email: lgp@tju.edu.cn
Zhu Liu
Email: liuzhu@mail.dlut.edu.cn
Jinhe Bi
Email: Jinhe.bi@campus.lmu.de
Posted on ServiceSetu Academics — Premier Platform for Academic Opportunities & Research Collaboration.
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