AIMC Topic: Predictive Value of Tests
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Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease.
Journal of the American College of Cardiology
Aug 27, 2024
BACKGROUND: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to detect biventricular pathophysiology. However, AI-ECG analysis remains underexplored in congenital heart disease (CHD).
Deep Learning-based Segmentation of Computed Tomography Scans Predicts Disease Progression and Mortality in Idiopathic Pulmonary Fibrosis.
American journal of respiratory and critical care medicine
Aug 15, 2024
Despite evidence demonstrating a prognostic role for computed tomography (CT) scans in idiopathic pulmonary fibrosis (IPF), image-based biomarkers are not routinely used in clinical practice or trials. To develop automated imaging biomarkers using ...
Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Aug 3, 2024
Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devices capable of detecting short episodes of arrhythmia are now widely available. Although it has recen...
Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.
Clinical cardiology
Aug 1, 2024
BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disea...
Retrospective Studies
Female
Risk Factors
Aged
Male
Humans
Machine Learning
Tomography, Optical Coherence
Stents
Middle Aged
Coronary Angiography
Coronary Vessels
Percutaneous Coronary Intervention
Risk Assessment
Plaque, Atherosclerotic
Coronary Artery Disease
China
Myocardial Infarction
Predictive Value of Tests
Research on predicting hematoma expansion in spontaneous intracerebral hemorrhage based on deep features of the VGG-19 network.
Postgraduate medical journal
Jul 18, 2024
PURPOSE: To construct a clinical noncontrastive computed tomography (NCCT) deep learning joint model for predicting early hematoma expansion (HE) after cerebral hemorrhage (sICH) and evaluate its predictive performance.
Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models.
American journal of respiratory and critical care medicine
Jul 15, 2024
The incidence of clinically undiagnosed obstructive sleep apnea (OSA) is high among the general population because of limited access to polysomnography. Computed tomography (CT) of craniofacial regions obtained for other purposes can be beneficial i...
Predictive value of circulating lymphocyte subsets and inflammatory indexes for neoadjuvant chemoradiotherapy response in rectal mucinous adenocarcinoma patients: A machine learning approach.
Cancer medicine
Jul 1, 2024
INTRODUCTION: In this study, we aimed to evaluate the predictive value of circulating lymphocyte subsets and inflammatory indexes in response to neoadjuvant chemoradiotherapy (NCRT) in patients with rectal mucinous adenocarcinomas (MACs).
Machine learning-based prediction of clinical outcomes after traumatic brain injury: Hidden information of early physiological time series.
CNS neuroscience & therapeutics
Jul 1, 2024
AIMS: To assess the predictive value of early-stage physiological time-series (PTS) data and non-interrogative electronic health record (EHR) signals, collected within 24 h of ICU admission, for traumatic brain injury (TBI) patient outcomes.
A method for predicting mortality in acute mesenteric ischemia: Machine learning.
Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES
Jul 1, 2024
BACKGROUND: This study aimed to develop and validate an artificial intelligence model using machine learning (ML) to predict hospital mortality in patients with acute mesenteric ischemia (AMI).
Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma.
Clinical and experimental dermatology
Jun 25, 2024
BACKGROUND: Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients.
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