115 citations · 119 across the 11 of their papers we have counts for
3 papers · 1 filter
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…
FairTabGen: High-Fidelity and Fair Synthetic Health Data Generation from Limited Samples
Nitish Nagesh, Salar Shakibhamedan, Mahdi Bagheri +4
Synthetic healthcare data generation offers a promising solution to research limitations in clinical settings caused by privacy and regulatory constraints. However, current synthet…
FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation
Nitish Nagesh, Ziyu Wang, Amir M. Rahmani
Synthetic data generation creates data based on real-world data using generative models. In health applications, generating high-quality data while maintaining fairness for sensiti…