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Special Session 6
AI-Driven Biomedical Signal Processing and Intelligent Healthcare

 

Organizer
Assoc. Prof. Goh Choon Hian, Universiti Tunku Abdul Rahman (UTAR), Malaysia


The rapid advancement of artificial intelligence (AI) and biomedical signal processing is transforming healthcare through more accurate disease detection, intelligent physiological monitoring, and personalized medical solutions. Emerging technologies, including machine learning, deep learning, wearable sensors, and advanced signal analysis, offer new opportunities to extract meaningful insights from complex biomedical data and support clinical decision-making. This special session aims to bring together researchers, engineers, and healthcare professionals to present recent advances in AI-driven biomedical signal processing and intelligent healthcare applications. Particular emphasis will be placed on innovative computational methods for physiological signal analysis, automated disease detection, real-time health monitoring, and AI-assisted diagnosis, as well as the development of intelligent and personalized healthcare systems.


Related topics:
1. AI and Deep Learning for Biomedical Signal Processing
2. Physiological Signal Analysis (ECG, EEG, EMG, PPG, etc.)
3. Machine Learning for Disease Detection and Diagnosis
4. Intelligent Healthcare Monitoring and Early Warning Systems
5. Wearable Sensors and IoT-Based Healthcare Applications
6. Biomedical Signal Feature Extraction and Classification
7. Multimodal Biomedical Data Fusion and Analysis
8. AI-Assisted Clinical Decision Support Systems
9. Remote Patient Monitoring and Telemedicine
10. Explainable and Trustworthy AI in Healthcare
11. Personalized and Predictive Healthcare Technologies
12. Real-Time Biomedical Signal Processing and Edge AI

 

 

Submission Guideline
Please submit your manuscript via Electronic Submission System (account is needed). (Please choose the session number when you make the submission.)

 

Important Dates
Submission of Full Papers/Abstract: Oct. 30, 2026
Notification of Review Result of Papers from Special Sessions: Nov. 15, 2026