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20192026
most citedTransformers in Healthcare: A Survey

176 citations · 224 across the 39 of their papers we have counts for

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5 papers · 1 filter

cs.AI2025★ 1 cited

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…

cs.AI2024★ 2 cited

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…

cs.AI2023

APRICOT-Mamba: Acuity Prediction in Intensive Care Unit (ICU): Development and Validation of a Stability, Transitions, and Life-Sustaining Therapies Prediction Model

Miguel Contreras, Brandon Silva, Benjamin Shickel +9

The acuity state of patients in the intensive care unit (ICU) can quickly change from stable to unstable. Early detection of deteriorating conditions can result in providing timely…

cs.AI2023★ 176 cited

Transformers in Healthcare: A Survey

Subhash Nerella, Sabyasachi Bandyopadhyay, Jiaqing Zhang +9

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly…

cs.AI2023★ 4 cited

AI-Enhanced Intensive Care Unit: Revolutionizing Patient Care with Pervasive Sensing

Subhash Nerella, Ziyuan Guan, Scott Siegel +5

The intensive care unit (ICU) is a specialized hospital space where critically ill patients receive intensive care and monitoring. Comprehensive monitoring is imperative in assessi…