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Found 6 papers, 0 papers with code
A multi-cohort study on prediction of acute brain dysfunction states using selective state space models
Our research fills these gaps in the existing literature by dynamically predicting delirium, coma, and mortality for 12-hour intervals throughout an ICU stay and validating on two public datasets.
Leveraging Computer Vision in the Intensive Care Unit (ICU) for Examining Visitation and Mobility
Likewise, while mobility can be an important indicator of recovery or deterioration in ICU patients, it is only captured sporadically or not captured at all.
APRICOT-Mamba: Acuity Prediction in Intensive Care Unit (ICU): Development and Validation of a Stability, Transitions, and Life-Sustaining Therapies Prediction Model
The acuity state of patients in the intensive care unit (ICU) can quickly change from stable to unstable.
The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)
In this study, we evaluated the impact of integrating mobility data collected from wrist-worn accelerometers with clinical data obtained from EHR for developing an AI-driven acuity assessment score.
Transformers in Healthcare: A Survey
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications.
Predicting risk of delirium from ambient noise and light information in the ICU
This study shows that ambient light and noise intensities are strong predictors of long-term delirium incidence in the ICU.
