[CFP] EA Track on Explainable and Trustworthy AI for Digital Health at ACM TRUST 2027 (Track 20)
Sagnik Dakshit
Dear Colleagues,
We are pleased to invite submissions to the Emerging Area Track on Explainable and Trustworthy AI for Digital Health (ETA-Digital Health - Track 20) at the ACM Conference on Trustworthy and Responsible AI and Computing Systems (ACM TRUST 2027).
Conference Dates: March 7–9, 2027
Location: Washington, DC, USA
Conference Website: https://eigtrust.acm.org/trust2027/
Track Website: https://eta-digital-health.vercel.app/
Important Dates
Abstract Registration: October 24, 2026
Paper Submission: October 31, 2026
Notification of Acceptance: December 31, 2026
Final Manuscript/Camera-Ready Submission: February 28, 2027
About the Track
The widespread adoption of artificial intelligence in digital and mobile health settings demands systems that are not only accurate, but also transparent, auditable, fair, reliable, and aligned with everyday use, remote-care workflows, and regulatory expectations.
ETA-Digital Health provides a dedicated forum for foundational and applied research at the intersection of explainable AI, trustworthy systems, and digital health. The track encompasses wearable biosignal intelligence, remote patient monitoring, rehabilitation technology, mobile health applications, and responsible AI governance for consumer-facing health technologies.
We welcome contributions from researchers, clinicians, engineers, practitioners, and policymakers working to advance safe, reliable, explainable, and human-centered AI across the full spectrum of digital and mobile health systems.
Topics of Interest
Topics include, but are not limited to:
Explainable AI for wearable and mobile health sensing
Multimodal biosignal fusion for continuous mobile health monitoring
Federated and on-device learning for wearable and IoT health sensors
Equity and the digital divide in health-technology adoption
Uncertainty quantification for continuous physiological sensing
Edge AI, hardware-based trust, secure enclaves, and security for wearable and VR/AR health devices
Agentic AI for remote monitoring and care coordination
Patient trust and human-in-the-loop design for remote monitoring
Benchmark datasets and evaluation frameworks for wearable and mobile health AI
Data ownership, governance, and software-as-a-medical-device regulatory pathways
AI-driven remote patient monitoring and mobile health systems
Trustworthy AI for rehabilitation, telehealth, and digital health delivery
Explainable AI for VR/AR-based digital health and rehabilitation
AI for smartphone-based digital therapeutics
Paper Submission and Publication
Manuscripts must be submitted in PDF format using the ACM two-column proceedings template:
https://www.acm.org/publications/proceedings-template
Full papers may not exceed nine pages, including appendices, figures, and tables generated using GenAI tools, but excluding the Generative AI Usage Disclosure section and references.
Submissions will undergo double-blind peer review. Authors must not reveal their identities or affiliations and should avoid obvious self-references.
Accepted papers will be published in the ACM Digital Library and are expected to be indexed in EI Compendex and Scopus.
Track Chairs
Dr. Sagnik Dakshit, Kennesaw State University
sdak...@kennesaw.edu
Dr. Ahmad P. Tafti, University of Pittsburgh
tafti...@pitt.edu
Dr. Ayse Tekes, Kennesaw State University
ate...@kennesaw.edu
We would greatly appreciate your help in sharing this call for papers with colleagues, students, collaborators, and relevant research communities.
We look forward to receiving your submissions and welcoming you to ACM TRUST 2027 in Washington, DC.
Best regards,
Track Chairs
EA Track on Explainable and Trustworthy AI for Digital Health (Track 20)
ACM TRUST 2027