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Deep learning model based on contrast-enhanced ultrasound for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma.
European radiology
Jul 27, 2024
OBJECTIVES: To establish and validate a non-invasive deep learning (DL) model based on contrast-enhanced ultrasound (CEUS) to predict vessels encapsulating tumor clusters (VETC) patterns in hepatocellular carcinoma (HCC).
Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.
European radiology
Jul 27, 2024
OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary...
Evaluating the effectiveness of a sliding window technique in machine learning models for mortality prediction in ICU cardiac arrest patients.
International journal of medical informatics
Jul 27, 2024
Extensive research has been devoted to predicting ICU mortality, to assist clinical teams managing critical patients. Electronic health records (EHR) contain both static and dynamic medical data, with the latter accumulating during ICU stays. Existin...
Development and validation of a machine learning framework for improved resource allocation in the emergency department.
The American journal of emergency medicine
Jul 27, 2024
OBJECTIVE: The Emergency Severity Index (ESI) is the most commonly used system in over 70% of all U.S. emergency departments (ED) that uses predicted resource utilization as a means to triage [1], Mistriage, which includes both undertriage and overtr...
Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.
Journal of thrombosis and thrombolysis
Jul 27, 2024
This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein thrombosis (DVT) based on patients' limb function, activities of daily living (ADL), clinical laborat...
Differentiation of tuberculous and brucellar spondylitis using conventional MRI-based deep learning algorithms.
European journal of radiology
Jul 27, 2024
PURPOSE: To investigate the feasibility of deep learning (DL) based on conventional MRI to differentiate tuberculous spondylitis (TS) from brucellar spondylitis (BS).
Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.
Scientific reports
Jul 27, 2024
The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of c...
Evaluation of the Factors Influencing Blood Transfusion during Minimally Invasive Direct Coronary Artery Bypass Surgery.
Cardiology
Jul 26, 2024
INTRODUCTION: The objective of this study was to analyze the blood transfusion factors of minimally invasive direct coronary artery bypass (MIDCAB) surgery using artificial intelligence.
Optimizing pain management in breast cancer care: Utilizing 'All of Us' data and deep learning to identify patients at elevated risk for chronic pain.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Jul 26, 2024
PURPOSE: The aim of the study was to develop a prediction model using deep learning approach to identify breast cancer patients at high risk for chronic pain.
Bloodstream infection: Derivation and validation of a reliable and multidimensional prognostic score based on a machine learning model (BLISCO).
American journal of infection control
Jul 26, 2024
BACKGROUND: A bloodstream infection (BSI) prognostic score applicable at the time of blood culture collection is missing.
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