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...
BACKGROUND: This study aimed to examine the accuracy with which multiple natural language processing artificial intelligence models could predict discharge and readmissions after general surgery.
INTRODUCTION: It is important for robotic surgery to be cost-effective, especially by reducing the length of stay (LOS). Therefore, we developed a protocol for day-case robot-assisted radical prostatectomy (RARP). This study aimed to validate this as...
Interest in home-based stroke rehabilitation mechatronics, which includes both robots and sensor mechanisms, has increased over the past 12 years. The COVID-19 pandemic has exacerbated the existing lack of access to rehabilitation for stroke survivor...
PURPOSE: Inpatient mortality is an important variable in epidemiology studies using claims data. In 2016, MarketScan data began obscuring specific hospital discharge status types for patient privacy, including inpatient deaths, by setting the values ...
PURPOSE: To report the trends, predictors, and patient outcomes of same-day discharge (SDD) versus non-SDD for robot-assisted laparoscopic radical prostatectomy (RALP).
BACKGROUND: This study aimed to examine the performance of machine learning algorithms for the prediction of discharge within 12 and 24 h to produce a measure of readiness for discharge after general surgery.
As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians detect less than 40% of delirium when using a validated screening tool. EEG is the criterion standa...
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