Course Content (Syllabus)
Introduction - general concepts - data science and ML - data exploration and visualization
Medical Data Management, quality and standards
Machine Learning – Theory – Lab
Deep learning – Theory – lab
AI & Medical Decision Support/Ethics and trustworthiness of AI
Medical image analysis and segmentation/characterization applications
Medical Imaging, Radiomics & AI in diagnosis and prognosis
Biomedical Signals - Biosignal collection and analysis
Patient Decision Support / Decision Support and Behavioral Informatics
AI Applications (Clinical Data, Biomarkers, Biological Data)
TN in the management of the patient's everyday life