Organizers

General Chair

Alex MH Kuo, PhD

Professor, School of Health Information Science, University of Victoria, Canada.
Chair, Special Interest Group on Big Data for Healthcare, Medicine and Biology, IEEE TCBD.

Co-Chairs

Juan C. Trujillo, PhD

Professor, Dept. Information Systems and Languages, University of Alicante, Spain.

Matteo Mantovani, PhD

Assistant Professor, Department of Computer Science, University of Verona, Italy.

Eliana Pastor, PhD

Assistant Professor, Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy.

Technical Program Committee

Elizabeth Borycki Professor University of Victoria, Canada.
Andre Kushniruk Professor University of Victoria, Canada.
Alex Thomo Professor  University of Victoria, Canada.
Abdul Roudsari Professor  University of Victoria, Canada.
Jia-Lin Liu Professor West China Hospital Sichuan University, Sichuan, China. 
Shu-Lin Wang Associate Professor National Taichung University of Science and Technology, Taiwan.
Damiano Carra Associate Professor Department of Computer Science, University of Verona, Italy. 
Dillon Chrimes Assistant Teaching Professor University of Victoria, Canada.
Bakhtiar Amen Lecturer Computer Science Department Centre of Artificial Intelligence University of Huddersfield, UK.
Hashim Abu-gellban Ph.D. Texas Tech University, USA.
Flavio Giobergia Ph.D. Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy.
Beatrice Amico Ph.D. Department of Computer Science, University of Verona, Italy.
Marta Lovino Post-Doc Department of Engineering, University of Modena and Reggio Emilia, Italy.
Jonas Bambi Ph.D. candidate Vancouver Island Health Authority, BC, canada.

Background

The healthcare and life sciences sector are among the most data-intensive industries in the world. Modern clinical information systems such as Electronic Health Records (EHRs), Computerized Physician Order Entry (CPOE), Laboratory Information Systems, Picture Archiving and Communication Systems (PACS), and medical sensors generate immense volumes of heterogeneous raw data daily. This vast accumulation, often referred to as Big Data in healthcare, holds significant potential for transforming the industry. Big Data Analytics (BDA) involves collecting, managing, and analyzing Healthcare Big Data to derive actionable insights that enhance patient outcomes, streamline healthcare operations, and fuel medical innovation.

Artificial Intelligence (AI) is revolutionizing healthcare by enhancing diagnostics, personalizing treatments, optimizing operations, and improving patient outcomes. AI-powered technologies leverage machine learning, deep learning, natural language processing (NLP), and robotics to analyze vast amounts of medical data, automate complex tasks, and support clinical decision-making.

Big Data Analytics in AI is reshaping healthcare by enabling intelligent decision-making, improving patient outcomes, and optimizing operational efficiency. As AI continues to evolve, its integration with Big Data will further enhance patient care, operational efficiency, and medical research, ultimately revolutionizing the healthcare industry.

Objectives & Research Topics

The primary goal of this multidisciplinary workshop was to bring together researchers and practitioners to discuss and identify emerging issues and explore innovative solutions for integrating AI into the Big Data Analytics process. We invite papers presenting original research on both theoretical and practical aspects of AI in Healthcare BDA. Topics of interest include, but are not limited to:

  • Big Data Analytics Infrastructure, methodologies and tools for healthcare
  • Standard Development for Healthcare Big Data Governance/Interoperability
  • Metadata for Healthcare Big Data Integration, Discovery and Interpretation
  • Visualization Analytics for Big Data in Biology, Medicine, and Healthcare
  • Ethics, Bias, and Explainability in Healthcare AI
  • AI and Big Data Integration for Personalized Medicine
  • AI-Powered Medical Imaging Analysis
  • AI for Remote Monitoring and Telehealth
  • AI-Driven Predictive Analytics in Healthcare

Keynote Speaker

In addition to the accepted papers, experts from industry and academia may be invited to give presentation relating to Health Big Data Analytics from their specific backgrounds and expertise.

Paper submission & presentation instructions

  • This workshop will be a hybrid event with both onsite and online participation through the Zoom Meeting platform.
  • We only accept papers that have not been previously published. Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (https://www.ieee.org/conferences/publishing/templates.html).
    Papers should be up to 10 pages (references included), in the IEEE 2-column format.

Submit your paper here!