4 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine
Michael S. Yao, Osbert Bastani, Alma Andersson +3
The goal of personalized medicine is to discover a treatment regimen that optimizes a patient's clinical outcome based on their personal genetic and environmental factors. However,…
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
Michael S. Yao, James C. Gee, Osbert Bastani
The goal of offline model-based optimization (MBO) is to propose new designs that maximize a reward function given only an offline dataset. However, an important desiderata is to a…
Evidence Is All You Need: Ordering Imaging Studies via Language Model Alignment with the ACR Appropriateness Criteria
Michael S. Yao, Allison Chae, Charles E. Kahn +4
Diagnostic imaging studies are an increasingly important component of the workup and management of acutely presenting patients. However, ordering appropriate imaging studies accord…
A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data
Yifan Wu, Yang Liu, Yue Yang +10
Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning of…
Generative Adversarial Model-Based Optimization via Source Critic Regularization
Michael S. Yao, Yimeng Zeng, Hamsa Bastani +3
Offline model-based optimization seeks to optimize against a learned surrogate model without querying the true oracle objective function during optimization. Such tasks are commonl…