AIMC Topic: Predictive Value of Tests

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Volume Measurements for Surveillance after Endovascular Aneurysm Repair using Artificial Intelligence.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery Sep 3, 2024
OBJECTIVE: Surveillance after endovascular aneurysm repair (EVAR) is suboptimal due to limited compliance and relatively large variability in measurement methods of abdominal aortic aneurysm (AAA) sac size after treatment. Measuring volume offers a m...
Blood Vessel Prosthesis Implantation Endovascular Procedures Computed Tomography Angiography Aortography Endovascular Aneurysm Repair Male Treatment Outcome Predictive Value of Tests Aortic Aneurysm, Abdominal Radiographic Image Interpretation, Computer-Assisted Humans Artificial Intelligence Software Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over
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Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.

Cardiovascular diabetology Sep 3, 2024
BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Humans Middle Aged Risk Assessment Deep Learning Diabetes Mellitus, Type 2 Adipose Tissue Predictive Value of Tests Prognosis Female Reproducibility of Results Risk Factors Aged Male Diabetic Angiopathies Coronary Angiography Vascular Calcification Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Coronary Artery Disease Pericardium Adiposity Epicardial Adipose Tissue Automation
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Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.

Circulation. Cardiovascular quality and outcomes Sep 2, 2024
BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to...
Cardiotoxicity Anthracyclines United States Artificial Intelligence Electrocardiography Retrospective Studies Predictive Value of Tests Female Ventricular Dysfunction, Left Risk Factors Trastuzumab Aged Male Ventricular Function, Left Stroke Volume Middle Aged Risk Assessment Antineoplastic Agents Time Factors Humans
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An unsupervised learning model based on CT radiomics features accurately predicts axillary lymph node metastasis in breast cancer patients: diagnostic study.

International journal of surgery (London, England) Sep 1, 2024
BACKGROUND: The accuracy of traditional clinical methods for assessing the metastatic status of axillary lymph nodes (ALNs) is unsatisfactory. In this study, the authors propose the use of radiomic technology and three-dimensional (3D) visualization ...
Humans Retrospective Studies Tomography, X-Ray Computed Female Lymph Nodes Lymphatic Metastasis Lymph Node Excision Axilla Unsupervised Machine Learning Aged Predictive Value of Tests Adult Breast Neoplasms Radiomics Middle Aged Imaging, Three-Dimensional
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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...
Hematoma Automation Male Middle Aged Risk Assessment Disease Progression Deep Learning China Time Factors Nomograms Cerebral Hemorrhage Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Radiomics Humans Decision Support Techniques Prognosis Retrospective Studies Tomography, X-Ray Computed
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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.
Pregnancy Trimester, First Diabetes, Gestational Glucose Tolerance Test Risk Factors Humans Young Adult Machine Learning Adult Algorithms Blood Glucose Pregnancy Body Mass Index Female Predictive Value of Tests Parity
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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...
Female Aged Male Middle Aged Predictive Value of Tests Humans Heart Diseases Machine Learning Algorithms
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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...
Cerebrospinal Fluid Leak Skull Base Encephalocele Adult Male Middle Aged Risk Assessment Deep Learning Predictive Value of Tests 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...
Thyroid Neoplasms Female Humans Ultrasonography Risk Factors Retrospective Studies ROC Curve Young Adult Predictive Value of Tests Lymph Nodes Male Lymphatic Metastasis Area Under Curve Risk Assessment Regression Analysis Adolescent 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 ...
Humans Risk Assessment Time Factors Lung Neoplasms Female Radiographic Image Interpretation, Computer-Assisted Machine Learning Treatment Outcome Neoplasm Recurrence, Local Risk Factors Decision Support Techniques Predictive Value of Tests Microwaves Aged Retrospective Studies Neoplasm Staging Margins of Excision Radiomics Tomography, X-Ray Computed Adenocarcinoma of Lung Male Clinical Decision-Making Ablation Techniques Middle Aged
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