TARGET AUDIENCE
Students (U.G., & P.G.), PhD Scholars, Faculty Members.
TOPICS
The IEEE SPS School on "AI-based Medical System Design for Biomedical Signals" may cover a wide range of topics related to the application of artificial intelligence in designing medical systems for analyzing and processing biomedical signals. Here are some potential topics that could be covered:
Introduction to AI in medical signal processing
Basics of biomedical signals (e.g., ECG, EEG, EMG, etc.)
Preprocessing and filtering techniques for biomedical signals
Feature extraction and selection for biomedical signals
Machine learning and Deep learning algorithms for medical signal classification
Convolutional neural networks (CNNs) for biomedical signal processing
Recurrent neural networks (RNNs) for time series analysis of biomedical signals
Generative models for medical signal synthesis and augmentation
Transfer learning and domain adaptation for medical signal analysis
Explainable AI for medical signal processing
Integration of AI in medical devices and systems
Wearable and implantable AI-enabled medical devices
Detection and classification of abnormal events in biomedical signals
Real-time processing of biomedical signals for clinical applications
Validation and evaluation of AI-based medical systems
Ethical considerations and regulatory challenges in AI-based medical systems
Case studies and applications of AI in specific medical domains
Future trends and challenges in AI-based medical system design for biomedical signals.