9 papers
Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation
Yuta Kobayashi, Pradyun Ramesh, Muhammad Ahmed Chaudhry +5
Vision-Language Models (VLMs) for radiology report generation are typically trained on retrospective clinical reports, which suffer from omission noise: clinically present findings…
One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
Zilin Jing, Vincent Jeanselme, Yuta Kobayashi +6
Clinical events captured in Electronic Health Records (EHR) are irregularly sampled and may consist of a mixture of discrete events and numerical measurements, such as laboratory v…
Aligning Probabilistic Beliefs under Informative Missingness: LLM Steerability in Clinical Reasoning
Yuta Kobayashi, Vincent Jeanselme, Shalmali Joshi
Large Language Models (LLMs) are increasingly deployed for clinical reasoning tasks, which inherently require eliciting calibrated probabilistic beliefs based on available evidence…
ICYM2I: The illusion of multimodal informativeness under missingness
Young Sang Choi, Vincent Jeanselme, Pierre Elias +1
Multimodal learning is of continued interest in artificial intelligence-based applications, motivated by the potential information gain from combining different data modalities. Ho…
Path-specific effects for pulse-oximetry guided decisions in critical care
Kevin Zhang, Yonghan Jung, Divyat Mahajan +2
Identifying and measuring biases associated with sensitive attributes is a crucial consideration in healthcare to prevent treatment disparities. One prominent issue is inaccurate p…
A pipeline for enabling path-specific causal fairness in observational health data
Aparajita Kashyap, Sara Matijevic, Noémie Elhadad +2
When training machine learning (ML) models for potential deployment in a healthcare setting, it is essential to ensure that they do not replicate or exacerbate existing healthcare…