AIMC Topic: Cohort Studies
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Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards.
Critical care (London, England)
Sep 5, 2023
BACKGROUND: Retrospective studies have demonstrated that the deep learning-based cardiac arrest risk management system (DeepCARS™) is superior to the conventional methods in predicting in-hospital cardiac arrest (IHCA). This prospective study aimed t...
Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.
European radiology
Sep 2, 2023
OBJECTIVES: We aimed to evaluate whether deep learning-based detection and quantification of brain metastasis (BM) may suggest treatment options for patients with BMs.
Novel parameters for predicting fluid responsiveness during the mini fluid challenge and ability of the cardiac power index: an observational cohort study.
Turkish journal of medical sciences
Aug 26, 2023
BACKGROUND/AIM: The percentage change in the stroke volume index (SVI) due to the mini fluid challenge (MFC) (MFC-ΔSVI%) is used commonly in daily practice. However, up to 20% of patients remain in the gray zone of this variable. Thus, it was aimed t...
Cohort profile for development of machine learning models to predict healthcare-related adverse events (Demeter): clinical objectives, data requirements for modelling and overview of data set for 2016-2018.
BMJ open
Aug 17, 2023
PURPOSE: In-hospital health-related adverse events (HAEs) are a major concern for hospitals worldwide. In high-income countries, approximately 1 in 10 patients experience HAEs associated with their hospital stay. Estimating the risk of an HAE at the ...
Automated Deep Learning-Based Segmentation of Abdominal Adipose Tissue on Dixon MRI in Adolescents: A Prospective Population-Based Study.
AJR. American journal of roentgenology
Aug 16, 2023
The prevalence of childhood obesity has increased significantly worldwide, highlighting a need for accurate noninvasive quantification of body fat distribution in children. The purpose of this study was to develop and test an automated deep learnin...
Prediction of Retear After Arthroscopic Rotator Cuff Repair Based on Intraoperative Arthroscopic Images Using Deep Learning.
The American journal of sports medicine
Aug 11, 2023
BACKGROUND: It is challenging to predict retear after arthroscopic rotator cuff repair (ARCR). The usefulness of arthroscopic intraoperative images as predictors of the ARCR prognosis has not been analyzed.
Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals.
PloS one
Aug 7, 2023
BACKGROUND: The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using health care usage for predicting mortality remains unexplored. The aim of this study was to investigate ...
Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.
Archives of gynecology and obstetrics
Jul 21, 2023
PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated...
Biochemical recurrence after chemohormonal therapy followed by robot-assisted radical prostatectomy in very-high-risk prostate cancer patients.
Journal of robotic surgery
Jul 19, 2023
Robot-assisted radical prostatectomy (RARP) has become one of the standard radical treatments for prostate cancer (PCa). A retrospective single-center cohort study was conducted on patients with PCa who underwent RARP at Gifu University Hospital betw...
A cost-effective model for training in Robot-Assisted Sacrocolpopexy.
International urogynecology journal
Jul 15, 2023
BACKGROUND: The number of robotically assisted sacrocolpopexy procedures are increasing; therefore, experienced clinicians are needed. Simulation-based cadaver models are challenging in aspects of cost and availability. Therefore, we need to look at ...
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