176 citations · 224 across the 39 of their papers we have counts for
12 papers · 1 filter
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…
DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR
Miguel Contreras, Sumit Kapoor, Jiaqing Zhang +7
Delirium is an acute confusional state that has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection of this condition could lead to more ti…
Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools
Yingbo Ma, Yukyeong Song, Jeremy A. Balch +12
As more clinical workflows continue to be augmented by artificial intelligence (AI), AI literacy among physicians will become a critical requirement for ensuring safe and ethical A…
Transparent AI: Developing an Explainable Interface for Predicting Postoperative Complications
Yuanfang Ren, Chirayu Tripathi, Ziyuan Guan +10
Given the sheer volume of surgical procedures and the significant rate of postoperative fatalities, assessing and managing surgical complications has become a critical public healt…
Global Contrastive Training for Multimodal Electronic Health Records with Language Supervision
Yingbo Ma, Suraj Kolla, Zhenhong Hu +11
Modern electronic health records (EHRs) hold immense promise in tracking personalized patient health trajectories through sequential deep learning, owing to their extensive breadth…
Federated learning model for predicting major postoperative complications
Yonggi Park, Yuanfang Ren, Benjamin Shickel +8
Background: The accurate prediction of postoperative complication risk using Electronic Health Records (EHR) and artificial intelligence shows great potential. Training a robust ar…
Temporal Cross-Attention for Dynamic Embedding and Tokenization of Multimodal Electronic Health Records
Yingbo Ma, Suraj Kolla, Dhruv Kaliraman +10
The breadth, scale, and temporal granularity of modern electronic health records (EHR) systems offers great potential for estimating personalized and contextual patient health traj…
Epidemiology, Trajectories and Outcomes of Acute Kidney Injury Among Hospitalized Patients: A Retrospective Multicenter Large Cohort Study
Esra Adiyeke, Yuanfang Ren, Shmuel Fogel +5
Background: Acute kidney injury (AKI) is a clinical syndrome affecting almost one fifth of hospitalized patients, as well as more than half of the patients who are admitted to the…
A multi-cohort study on prediction of acute brain dysfunction states using selective state space models
Brandon Silva, Miguel Contreras, Sabyasachi Bandyopadhyay +8
Assessing acute brain dysfunction (ABD), including delirium and coma in the intensive care unit (ICU), is a critical challenge due to its prevalence and severe implications for pat…
Leveraging Computer Vision in the Intensive Care Unit (ICU) for Examining Visitation and Mobility
Scott Siegel, Jiaqing Zhang, Sabyasachi Bandyopadhyay +5
Despite the importance of closely monitoring patients in the Intensive Care Unit (ICU), many aspects are still assessed in a limited manner due to the time constraints imposed on h…
Acute kidney injury prediction for non-critical care patients: a retrospective external and internal validation study
Esra Adiyeke, Yuanfang Ren, Benjamin Shickel +12
Background: Acute kidney injury (AKI), the decline of kidney excretory function, occurs in up to 18% of hospitalized admissions. Progression of AKI may lead to irreversible kidney…
Evaluation of General Large Language Models in Contextually Assessing Semantic Concepts Extracted from Adult Critical Care Electronic Health Record Notes
Darren Liu, Cheng Ding, Delgersuren Bold +16
The field of healthcare has increasingly turned its focus towards Large Language Models (LLMs) due to their remarkable performance. However, their performance in actual clinical ap…