6 citations · 10 across the 6 of their papers we have counts for
6 papers
Data reuse enables cost-efficient randomized trials of medical AI models
Michael Nercessian, Wenxin Zhang, Alexander Schubert +4
Randomized controlled trials (RCTs) are indispensable for establishing the clinical value of medical artificial-intelligence (AI) tools, yet their high cost and long timelines hind…
Mean-field Chaos Diffusion Models
Sungwoo Park, Dongjun Kim, Ahmed Alaa
In this paper, we introduce a new class of score-based generative models (SGMs) designed to handle high-cardinality data distributions by leveraging concepts from mean-field theory…
Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding
Shenghuan Sun, Alexander Schubert, Gregory M. Goldgof +4
Vision-Language Models (VLM) can support clinicians by analyzing medical images and engaging in natural language interactions to assist in diagnostic and treatment tasks. However,…
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists
Yulu Gan, Sungwoo Park, Alexander Schubert +2
Recent advances in generative diffusion models have enabled text-controlled synthesis of realistic and diverse images with impressive quality. Despite these remarkable advances, th…
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback
Shenghuan Sun, Gregory M. Goldgof, Atul Butte +1
Generative models capable of capturing nuanced clinical features in medical images hold great promise for facilitating clinical data sharing, enhancing rare disease datasets, and e…
Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care
Ali Shirali, Alexander Schubert, Ahmed Alaa
Medical treatments often involve a sequence of decisions, each informed by previous outcomes. This process closely aligns with reinforcement learning (RL), a framework for optimizi…