AIMC Topic: Patient Discharge
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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.
Early-stage neutralizing antibody level associated with the re-positive risk of Omicron SARS-CoV-2 RNA in patients recovered from COVID-19.
Diagnostic microbiology and infectious disease
Dec 17, 2023
Post-discharge re-positivity of Omicron SARS-CoV-2 is challenging for the sufficient control of this pandemic. However, there are few studies about the risk of re-positivity. We aimed to explore the association of neutralizing antibodies (nAbs, AU/mL...
Assessing Decision Regret in Patients with Same-Day Discharge Pathway After Robot-Assisted Radical Prostatectomy.
Journal of endourology
Nov 30, 2023
After the introduction of same-day discharge (SDD) pathways for various surgeries, these pathways have demonstrated comparable complication rates and a reduced overall cost of care. Outpatient robot-assisted radical prostatectomy (RARP) is introduce...
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