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...
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 ...
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 ...
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, ...
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 ...
OBJECTIVES: To predict the functional outcome of patients with intracerebral hemorrhage (ICH) using deep learning models based on computed tomography (CT) images.
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...
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...
IEEE journal of biomedical and health informatics
Oct 5, 2023
This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50 K, 16 K and 378 K pairs of report and summary that are derived from MIMIC-III, respectively. We implement convincing baselines o...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.