AIMC Topic: Predictive Value of Tests

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Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 31, 2024
BACKGROUND: Early prediction of hematoma expansion (HE) is important for the development of therapeutic strategies for spontaneous intracerebral hemorrhage (sICH). Radiomics can help to predict early hematoma expansion in intracerebral hemorrhage. Ho...
Radiographic Image Interpretation, Computer-Assisted Radiomics Hematoma Male Middle Aged Automation Risk Assessment Female Disease Progression Reproducibility of Results Deep Learning Humans Risk Factors China Decision Support Techniques Time Factors Aged Prognosis Nomograms Aged, 80 and over Retrospective Studies Cerebral Hemorrhage Tomography, X-Ray Computed Predictive Value of Tests
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The early prediction of gestational diabetes mellitus by machine learning models.

BMC pregnancy and childbirth Aug 31, 2024
BACKGROUND: We aimed to determine the best-performing machine learning (ML)-based algorithm for predicting gestational diabetes mellitus (GDM) with sociodemographic and obstetrics features in the pre-conceptional period.
Body Mass Index Predictive Value of Tests Pregnancy Trimester, First Diabetes, Gestational Glucose Tolerance Test Female Humans Parity Machine Learning Risk Factors Algorithms Young Adult Pregnancy Adult Blood Glucose
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Refining heart disease prediction accuracy using hybrid machine learning techniques with novel metaheuristic algorithms.

International journal of cardiology Aug 30, 2024
Early diagnosis of heart disease is crucial, as it's one of the leading causes of death globally. Machine learning algorithms can be a powerful tool in achieving this goal. Therefore, this article aims to increase the accuracy of predicting heart dis...
Algorithms Female Aged Male Middle Aged Heart Diseases Humans Predictive Value of Tests Machine Learning
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Deep learning to predict risk of lateral skull base cerebrospinal fluid leak or encephalocele.

International journal of computer assisted radiology and surgery Aug 29, 2024
PURPOSE: Skull base features, including increased foramen ovale (FO) cross-sectional area, are associated with lateral skull base spontaneous cerebrospinal fluid (sCSF) leak and encephalocele. Manual measurement requires skill in interpreting imaging...
Adult Male Middle Aged Risk Assessment Deep Learning Predictive Value of Tests Cerebrospinal Fluid Leak Skull Base Encephalocele Humans Retrospective Studies Tomography, X-Ray Computed Female Aged
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Prediction model for lateral lymph node metastasis of papillary thyroid carcinoma in children and adolescents based on ultrasound imaging and clinical features: a retrospective study.

BMC medical imaging Aug 29, 2024
BACKGROUND: The presence of lateral lymph node metastases (LNM) in paediatric patients with papillary thyroid cancer (PTC) is an independent risk factor for recurrence. We aimed to identify risk factors and establish a prediction model for lateral LN...
Male Risk Assessment Adolescent Thyroid Neoplasms Ultrasonography ROC Curve Lymph Nodes Lymphatic Metastasis Regression Analysis Predictive Value of Tests Area Under Curve Humans Retrospective Studies Female Risk Factors Young Adult Reference Values Thyroid Cancer, Papillary Predictive Learning Models
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Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Journal of vascular and interventional radiology : JVIR Aug 28, 2024
PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical ...
Neoplasm Recurrence, Local Microwaves Margins of Excision Adenocarcinoma of Lung Ablation Techniques Aged Decision Support Techniques Radiomics Time Factors Humans Retrospective Studies Male Lung Neoplasms Machine Learning Tomography, X-Ray Computed Middle Aged Treatment Outcome Risk Assessment Clinical Decision-Making Predictive Value of Tests Female Neoplasm Staging Risk Factors Radiographic Image Interpretation, Computer-Assisted
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Improved detection of small pulmonary embolism on unenhanced computed tomography using an artificial intelligence-based algorithm - a single centre retrospective study.

The international journal of cardiovascular imaging Aug 28, 2024
To preliminarily verify the feasibility of a deep-learning (DL) artificial intelligence (AI) model to localize pulmonary embolism (PE) on unenhanced chest-CT by comparison with pulmonary artery (PA) CT angiography (CTA). In a monocentric study, we re...
Adult Male Middle Aged Deep Learning Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Feasibility Studies Pulmonary Embolism Computed Tomography Angiography Pulmonary Artery Incidental Findings Humans Algorithms
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Electrocardiogram-Based Artificial Intelligence to Discriminate Cardioembolic Stroke and Stratify Risk of Atrial Fibrillation After Stroke.

Circulation. Arrhythmia and electrophysiology Aug 28, 2024
Humans Artificial Intelligence Female Risk Factors Aged Male Atrial Fibrillation Middle Aged Heart Rate Risk Assessment Embolic Stroke Electrocardiography Predictive Value of Tests Stroke
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Deep learning model for intravascular ultrasound image segmentation with temporal consistency.

The international journal of cardiovascular imaging Aug 27, 2024
This study was conducted to develop and validate a deep learning model for delineating intravascular ultrasound (IVUS) images of coronary arteries.Using a total of 1240 40-MHz IVUS pullbacks with 191,407 frames, the model for lumen and external elast...
Image Interpretation, Computer-Assisted Coronary Vessels Plaque, Atherosclerotic Retrospective Studies Female Reproducibility of Results Aged Male Middle Aged Humans Deep Learning Prognosis Time Factors Predictive Value of Tests Ultrasonography, Interventional Coronary Artery Disease
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Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.

Journal of the American Heart Association Aug 27, 2024
BACKGROUND: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke o...
Databases, Factual Retrospective Studies Female Risk Factors Aged Aged, 80 and over Humans Machine Learning Predictive Value of Tests Stroke Stents Endovascular Procedures Femoral Artery Male Carotid Stenosis Middle Aged Risk Assessment Time Factors Treatment Outcome
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