most citedPredicting risk of delirium from ambient noise and light information in the ICU

3 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023

The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)

Jessica Sena, Mohammad Tahsin Mostafiz, Jiaqing Zhang +9

Acuity assessments are vital in critical care settings to provide timely interventions and fair resource allocation. Traditional acuity scores rely on manual assessments and docume…

cs.LG2023

Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures

Yuanfang Ren, Yanjun Li, Tyler J. Loftus +9

Initial hours of hospital admission impact clinical trajectory, but early clinical decisions often suffer due to data paucity. With clustering analysis for vital signs within six h…

cs.LG20231 cited

Transformer Models for Acute Brain Dysfunction Prediction

Brandon Silva, Miguel Contreras, Tezcan Ozrazgat Baslanti +5

Acute brain dysfunctions (ABD), which include coma and delirium, are prevalent in the ICU, especially among older patients. The current approach in manual assessment of ABD by care…

cs.LG20233 cited

Predicting risk of delirium from ambient noise and light information in the ICU

Sabyasachi Bandyopadhyay, Ahna Cecil, Jessica Sena +8

Existing Intensive Care Unit (ICU) delirium prediction models do not consider environmental factors despite strong evidence of their influence on delirium. This study reports the f…

q-bio.QM20231 cited

Computable Phenotypes to Characterize Changing Patient Brain Dysfunction in the Intensive Care Unit

Yuanfang Ren, Tyler J. Loftus, Ziyuan Guan +7

In the United States, more than 5 million patients are admitted annually to ICUs, with ICU mortality of 10%-29% and costs over $82 billion. Acute brain dysfunction status, delirium…

q-bio.QM2023

Clinical Courses of Acute Kidney Injury in Hospitalized Patients: A Multistate Analysis

Esra Adiyeke, Yuanfang Ren, Ziyuan Guan +4

Objectives: We aim to quantify longitudinal acute kidney injury (AKI) trajectories and to describe transitions through progressing and recovery states and outcomes among hospitaliz…