AIMC Topic: Patient Discharge
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Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).
Internal and emergency medicine
Jun 22, 2024
Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have previously been derived to predict which patients are nearing discharge based upon ward round notes. In...
Use of machine learning to identify protective factors for death from COVID-19 in the ICU: a retrospective study.
PeerJ
Jun 12, 2024
BACKGROUND: Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the ...
A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.
International journal of nursing studies
May 9, 2024
BACKGROUND: ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their ...
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission.
Computer methods and programs in biomedicine
Apr 10, 2024
BACKGROUND AND OBJECTIVE: Critically ill children may suffer from impaired neurocognitive functions years after ICU (intensive care unit) discharge. To assess neurocognitive functions, these children are subjected to a fixed sequence of tests. Underg...
Predicting the Severity and Discharge Prognosis of Traumatic Brain Injury Based on Intracranial Pressure Data Using Machine Learning Algorithms.
World neurosurgery
Mar 20, 2024
OBJECTIVE: This study aimed to explore the potential of employing machine learning algorithms based on intracranial pressure (ICP), ICP-derived parameters, and their complexity to predict the severity and short-term prognosis of traumatic brain injur...
Generative Artificial Intelligence to Transform Inpatient Discharge Summaries to Patient-Friendly Language and Format.
JAMA network open
Mar 4, 2024
IMPORTANCE: By law, patients have immediate access to discharge notes in their medical records. Technical language and abbreviations make notes difficult to read and understand for a typical patient. Large language models (LLMs [eg, GPT-4]) have the ...
Study of medium and long-term free flow capacity and queue discharge rates on roads.
PloS one
Feb 28, 2024
With the rise in vehicle ownership, traffic congestion has emerged as a major barrier to urban progress, making the study and optimization of urban road capacity exceedingly crucial. The research on the medium and long-term free-flowing capacity and ...
Machine learning decision support model for discharge planning in stroke patients.
Journal of clinical nursing
Feb 15, 2024
BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, ...
Patient satisfaction analysis of robot-assisted minimally invasive adrenalectomy: a single-center retrospective study.
Journal of robotic surgery
Jan 17, 2024
The objective of this study is to compare the satisfaction of patients undergoing robot-assisted retroperitoneal laparoscopy adrenalectomy under the ambulatory mode and conventional mode. Basic information and clinical data of patients who underwent ...
CT-based deep learning model for predicting hospital discharge outcome in spontaneous intracerebral hemorrhage.
European radiology
Dec 21, 2023
OBJECTIVES: To predict the functional outcome of patients with intracerebral hemorrhage (ICH) using deep learning models based on computed tomography (CT) images.
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