Under the framework of the Community of Practice: “Health Data for Robust Medical AI,” we are pleased to announce an upcoming webinar titled “Generative AI for Synthetic Health Data.” Scheduled for February 27th from 10:30 to 12:30, this event will feature experts presenting advanced methodologies aimed at ensuring the quality, reliability, and clinical relevance of synthetic data.
During the session, discussions will center on innovative approaches to data auditing and evaluation, incorporating open-source tools to assess both real and synthetic datasets across various modalities. The webinar will also delve into both qualitative and quantitative methods for validating synthetic medical data, highlighting the importance of human-in-the-loop processes in enhancing the usability and trustworthiness of medical AI applications.
Furthermore, the session will address techniques for generating high-fidelity synthetic biomedical signals, such as realistic ECG and electrocorticography signals, which are critical for advancing machine learning applications in healthcare. In addition, the webinar will explore privacy-preserving methods for clinical data synthesis, utilizing deep generative models to create synthetic datasets that support early detection of critical health conditions while safeguarding patient privacy.
This event serves as a vital platform for discussing emerging challenges and opportunities in synthetic data for healthcare, with valuable insights from both researchers and industry leaders. We invite all members of the community of practice to join us for this informative and forward-thinking session.
