PHAROS AI Factory announced the 8th Course of its Training Series, with the title “Generative Modeling in Medical Data“, under the AI4Health Topic, that successfully took place on March 23rd, 2026.
Presentation language: Greek
Audience: This course was intended for students in Computer Science and Medical Sciences, as well as Researchers.
Description: This course introduced key concepts and methodologies for working with healthcare and medical data and generating synthetic datasets for research and Machine Learning applications. It began with an overview of healthcare data types and characteristics, including structured tabular data from electronic health records and medical imaging data such as MRIs and EEGs. The course presented traditional statistical approaches for synthetic data generation and data balancing, including techniques such as SMOTE, ADASYN, and other resampling methods commonly used to address class imbalance. It also covered modern Deep Learning approaches for Generative Modeling, including autoencoders and GANs for synthesizing realistic tabular and visual medical data. Finally, it discussed applications, benefits, and challenges of synthetic data in healthcare.
Learning Objectives
Gain a deeper understanding of synthetic data generation techniques applied in medical data.
Learning Outcomes:
- Analyze synthetic data generation techniques.
- Explore various data types utilized in healthcare.
- MRI processing and data generation techniques for medical and ML applications.
The course’s presentation material can be found here.
The course’s recordings can be found here.
