21st IEEE International Workshop on e-Health Systems & Web Technologies (ESAS 2026)

COMPSAC 2026 Theme: “Agentic AI: Innovative Software, Computing Paradigms, and Applications for Migrating from Reactive Models to Proactive Systems”

We invite academics, practitioners, and technology experts to submit their original research on innovative technologies, advanced systems, and transformative solutions in the field of digital health to ESAS 2026. This workshop aims to provide a platform to discuss how AI- supported advanced technological solutions are shaping the future of healthcare. The following topics are included, but are not limited to, the areas of interest listed below:

Track 1: Smart Health and Applications

Health Management and Analytics; Big Data; IoT (Internet of Things) and IoE (Internet of Everything) for Health; IoT Medical Devices; Electronic Health Records; Knowledge Management; Machine Learning; Data Mining; Text Mining; Social Media Applications and Services; Clinical Decision Support Systems; Expert Systems; Software Architectures for Healthcare; Semantic Web Technologies; Biomedical Software Solutions; Health Informatics; Modeling of Health Services; Security, Privacy, and Protection of Personal Health Data; Wearable Devices; Telecare and Telehealth; Home Monitoring Systems; Advanced
Computing Techniques; Active and Healthy Aging; Blockchain; IoT, Fog, and Cloud Computing; Wireless Body Area Sensor Networks; and Energy Efficiency and Communication in IoT Devices.

Track 2: Artificial Intelligence, Web Technologies, and Data (AIWD)

Data Science and Machine Learning (ML) Models and Applications; ML-Based Schema Matching, Instance Matching, Search, and Retrieval; Data Mining and Applications; Deep Learning and Applications; Big Data Analytics and Applications; Information Retrieval and Applications; Linked Data; Data-Driven Services and Applications; Semantic Web, Ontology, and Web Services; Data Management and Analytics; Cyber-Physical Systems; Smart Distributed Systems, Edge Computing, and Streaming Data Analysis; Multi-Agent Systems; and Other Smart Applications and Solutions (e.g., Smart City, Smart Home, etc.).

Track 3: Generative Pre-trained Transformer Models in e-Health, Web, and Recommendation Systems (GenLLM)

Methods and Applications of Generative AI such as ChatGPT, Amazon, Google, DeepMind, and Others in Health (e.g., Psychotherapy, Elderly Care, Protein Synthesis, Health Education, Machine-Assisted Surgery, Virtual Health Support, Accurate Diagnosis, etc.); Advanced Model Architectures for LLMs; Federated Learning for LLMs; LLMs in Chatbots, Content Generation, Feedback Systems, etc.; Natural Language Understanding and Generation Tasks Using LLMs (e.g., Storytelling, Marketing, Copywriting, etc.); LLMs for Recommendation Systems and Solutions; LLMs in Information Management and Filtering; LLMs on Social Networks; LLMs in Recommender Systems; Context-Aware Recommenders; LLMs in Human Decision-Making Solutions and Applications; Case Studies of Generative AI; and Collaborative Decision-
Making Frameworks.

Track 4: Innovative Solutions in Telehealth and Remote Patient Monitoring (TeleHealth)

Telehealth Technologies and Applications; Remote Patient Monitoring Systems; Wearable Health Devices and Their Impact; Mobile Health (m-Health) Applications; Telemedicine Best Practices; Integration of Artificial Intelligence in Telehealth; Data Privacy and Security in Remote Health Solutions; Patient Engagement and Experience in Telehealth; Telehealth Policy and Regulation; Virtual Reality (VR) and Augmented Reality (AR) in Patient Care; Cost-Effectiveness of Telehealth Solutions; Challenges and Opportunities in Telehealth Adoption; and Case Studies of Successful Telehealth Implementations.