DM-SmartHealth 2026

Workshop Description

In the era of healthcare digitalization, the integration of smart technologies plays a crucial role in transforming patient care significantly. This workshop seeks to unite experts, researchers, and professionals across various disciplines to explore the latest innovations in smart health solutions. By fostering discussions, sharing insights, and encouraging collaboration, the workshop serves as a unique platform at the forefront of smart health technologies. The primary goals are to advance the field, contribute to the development of more effective and secure solutions, and address ethical considerations.

MOBILE & WEARABLE TECHNOLOGIES

Investigation of new smart health applications based on mobile and wearable technologies.

AI FOR HEALTHCARE

Novel techniques to optimize Artificial Intelligence models for digital health solutions.

DIGITAL PHENOTYPING

Iidentification of patterns, trends, and potential indicators related to mental and physical health.

This year, the workshop will expand its focus to include cutting-edge topics, such as the use of Large Language Models (LLMs) in digital health applications, addressing the challenges of integrating these models in real-time healthcare solutions. The workshop will also delve into critical areas like context-aware behavioral modeling, the use of AI for early diagnosis, remote monitoring, and decision support systems, as well as privacy and security concerns in health data. Participants will have the opportunity to discuss and share insights on a wide range of topics, fostering cross-disciplinary collaboration aimed at advancing the state of the art in smart health systems.

By engaging in discussions on these emerging topics, the workshop will contribute to the development of more efficient, reliable, and secure digital health solutions that are crucial for improving patient outcomes and revolutionizing healthcare delivery.

The 3rd IEEE Workshop on Digital and Mobile Smart Health Systems (DM-SMARTHEALTH 2026) will be held in conjunction with the 12th International Conference on Smart Computing (SMARTCOMP 2026) 22th - 25th June, 2026 in Messina, Italy.

Workshop papers will be included and indexed in the IEEE digital libraries (Xplore).

For additional information, read the Call for Papers or visit the SMARTCOMP 2026 website.

Call for Papers

As the healthcare landscape undergoes a digital transformation, integrating smart technologies plays a pivotal role in revolutionizing patient care. This workshop aims to bring together experts, researchers, and professionals from different research fields to delve into the latest advancements in smart health solutions, addressing critical topics that span from context-aware behavioral models, smart healthcare applications based on mobile and wearable technologies, digital phenotyping, novel techniques to optimize and develop more robust and reliable Artificial Intelligence models for digital health solutions, up to ethical challenges and privacy/security issues. This workshop provides a unique platform for participants to engage in discussions, share insights, and collaborate on the forefront of smart health technologies. By exploring these diverse topics, we aim to advance the field, ultimately contributing to the development of more effective, secure, and ethical smart health solutions

Relevant topics include but are not limited to:

Context-aware behavioral modeling techniques
Innovative approaches for collecting, labeling, and validating multimodal health and behavioral data
Novel smart health applications for early diagnosis, remote monitoring, and decision support systems based on wearable and mobile technologies
Middleware solutions for smart health and care systems
Decentralized architectures for mobile health solutions
Federated, Distributed, and Personalized learning solutions for privacy-preserving smart health
AI optimization techniques for smart and mobile health systems
Digital phenotyping: identification of novel digital biomarkers from IoT and commercial smart/wearable devices
Human-computer interaction solutions to support smart health applications
Social interaction analysis from personal mobile devices and social media
Synthetic data generation to support faster development of novel and robust AI solutions for digital healthcare
Causal AI for healthcare and precision medicine
The use of Large Language Models (LLMs) in digital health: Applications in patient communication, decision support, and predictive modeling
Challenges of deploying LLMs in mobile health systems: Issues of data privacy, model accuracy, and real-time performance
Novel explainable AI approaches to improve trustworthiness in digital healthcare systems
Security, privacy, and ethical challenges in smart health applications

Papers including new datasets and clinical/on-the-field validations will be highly appreciated.

Submission and Registration

Authors are invited to submit technical or theoretical papers for presentation at the workshop, describing original, previously unpublished work, which is not currently under review by another workshop, conference, or journal. Papers should present novel perspectives within the general scope of the workshop. Accepted workshop papers will be included and indexed in the IEEE digital libraries (Xplore).

Papers may be no more than 6 pages in length, including references. Papers above the page limits will not be considered for review or publication. All papers must be typeset in double-column IEEE format using 10pt fonts on US letter paper, with all fonts embedded. The IEEE LaTeX and Microsoft Word templates, as well as related information, can be found on the IEEE website.

Papers submission must be made via EDAS using the following link: https://edas.info/N34463.

It is a requirement that all the authors listed in the submitted paper are also listed in EDAS. The author section of EDAS will be locked after the workshop submission deadline to ensure that conflict of interest can be properly enforced during the review process. If the list of authors differs between the paper and EDAS, the paper may not be reviewed. Each accepted workshop paper requires a full SMARTCOMP registration (no registration is available for workshops only) and in-person presentation. Papers that are not presented at the workshop will not be published in the proceedings.

IMPORTANT DATES

Paper submission: ~~March 9th, 2026~~ March 23th, 2026
Paper notification: April 29th, 2026
Camera ready deadline: May 8th, 2026

Program

Location: Aula Cannizzaro (Main building)

Italy time	Description
14:00 - 14:10	Welcome from the Chairs Dr. Mattia Giovanni Campana (National Research Council of Italy), Prof. Nikil Dutt (University of California, Irvine, USA), and Prof. John Michael Templeton (University of South Florida, USA)
	Session 1 - Sensing, Monitoring and Clinical AI
14:10 - 14:45	A Machine Learning Approach for Sleep Apnea Detection Using Unobtrusive In-Bed Sensors Ricky Marinsalda (University of Pisa, Italy); Eleonora Melissa (Institute of Clinical Physiology, National Research Council, Italy); Carlotta Marinai and Lucia Arcarisi (Università di Pisa, Italy); Francesco Bossi (University of Pisa, Italy); Pasquale Bufano (National Research Council, Italy); Francesco Di Rienzo and Gianluca Rho (University of Pisa, Italy); Michele Zanoletti (IFC CNR, Italy); Alberto Greco (Università di Pisa, Italy); Carlo Vallati (University of Pisa, Italy); Nicola Carbonaro (Università di Pisa, Italy); Marco Laurino (National Research Council, Italy); Alessandro Tognetti (University of Pisa, Italy)
14:45 - 15:20	Robust Wearable Stress Detection using Physiological Feature Engineering and Subject-Independent Evaluation Paul Ben O'brien, Malik Muhammad Qirtas and Andrea Visentin (University College Cork, Ireland)
15:20 - 15:55	CLICK-SAM: A CLinical Interactive Click-based Kit for Digital Breast Tomosynthesis Segmentation Giada Anastasi, Giulio Del Corso, Michela Franchini, Sabrina Molinaro and Stefania Pieroni (Italian National Research Council, Italy)
	Session 2 - Large Language Models for Healthcare
16:05 - 16:40	Multimodal-to-Semantics Large Language Model Framework for Loneliness Assessment Chenxin Chen and Iman Azimi (University of Turku, Finland); Amir M. Rahmani (University of California, Irvine, USA); Pasi Liljeberg (University of Turku, Finland)
16:40 - 17:15	RamanLLM: Reprogramming Frozen Large Language Models for Raman Spectral Analysis Álvaro García (University College Cork, Ireland); Simone Innocente (Tyndall National Institute, Ireland); Nicola Rossberg, Malik Muhammad Qirtas and Andrea Visentin (University College Cork, Ireland)