7 papers
A Knowledge-Injection Framework for Zero-Shot Adaptation of LLMs to Delirium Prediction
Jessica Sena, Shesadree Priyadarshani, Miguel Contreras +4
Large language models show promise for clinical prediction, but zero-shot performance on specialized tasks is limited by incomplete domain knowledge, especially for smaller locally…
Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring
Jiaqing Zhang, Sandeep Elluri, Bhanu Cherukuvada +7
Multimodal large language models (LLMs) are increasingly explored as automated evaluators in clinical settings, yet their scoring behavior on ordinal clinical scales remains poorly…
Quantifying Circadian Desynchrony in ICU Patients and Its Association with Delirium
Yuanfang Ren, Andrea E. Davidson, Jiaqing Zhang +6
Background: Circadian desynchrony characterized by the misalignment between an individual's internal biological rhythms and external environmental cues, significantly affects vario…
MELON: Multimodal Mixture-of-Experts with Spectral-Temporal Fusion for Long-Term Mobility Estimation in Critical Care
Jiaqing Zhang, Miguel Contreras, Jessica Sena +8
Patient mobility monitoring in intensive care is critical for ensuring timely interventions and improving clinical outcomes. While accelerometry-based sensor data are widely adopte…
MANDARIN: Mixture-of-Experts Framework for Dynamic Delirium and Coma Prediction in ICU Patients: Development and Validation of an Acute Brain Dysfunction Prediction Model
Miguel Contreras, Jessica Sena, Andrea Davidson +9
Acute brain dysfunction (ABD) is a common, severe ICU complication, presenting as delirium or coma and leading to prolonged stays, increased mortality, and cognitive decline. Tradi…
MANGO: Multimodal Acuity traNsformer for intelliGent ICU Outcomes
Jiaqing Zhang, Miguel Contreras, Sabyasachi Bandyopadhyay +9
Estimation of patient acuity in the Intensive Care Unit (ICU) is vital to ensure timely and appropriate interventions. Advances in artificial intelligence (AI) technologies have si…