AIMC Topic: Predictive Value of Tests
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Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy.
Microvascular research
Aug 13, 2024
Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions within various organs such as the lungs, liver, and brain of living subjects. In medical imaging, edge detection is used to accurately identify and deli...
Machine learning-based model to predict composite thromboembolic events among Chinese elderly patients with atrial fibrillation.
BMC cardiovascular disorders
Aug 13, 2024
OBJECTIVE: Accurate prediction of survival prognosis is helpful to guide clinical decision-making. The aim of this study was to develop a model using machine learning techniques to predict the occurrence of composite thromboembolic events (CTEs) in e...
Improved robustness for deep learning-based segmentation of multi-center myocardial perfusion cardiovascular MRI datasets using data-adaptive uncertainty-guided space-time analysis.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Aug 12, 2024
BACKGROUND: Fully automatic analysis of myocardial perfusion cardiovascular magnetic resonance imaging datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart disease. Developing deep learning t...
Assessment of EMR ML Mining Methods for Measuring Association between Metal Mixture and Mortality for Hypertension.
High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension
Aug 12, 2024
INTRODUCTION: There are limited data available regarding the connection between heavy metal exposure and mortality among hypertension patients.
Predicting Intracranial Aneurysm Rupture: A Multifactor Analysis Combining Radscore, Morphology, and PHASES Parameters.
Academic radiology
Aug 10, 2024
RATIONALE AND OBJECTIVES: We aimed at developing and validating a nomogram and machine learning (ML) models based on radiomics score (Radscore), morphology, and PHASES to predict intracranial aneurysm (IA) rupture.
Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertainty.
The international journal of cardiovascular imaging
Aug 10, 2024
Left ventricular (LV) geometric patterns aid clinicians in the diagnosis and prognostication of various cardiomyopathies. The aim of this study is to assess the accuracy and reproducibility of LV dimensions and wall thickness using deep learning (DL)...
Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.
Cardiovascular diabetology
Aug 10, 2024
BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Diagnosis of this complication of DM is time-consuming and not routinely performed in the clinical prac...
Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: A radiomics and deep learning analysis on longitudinal DCE-MRI data.
Breast (Edinburgh, Scotland)
Aug 9, 2024
PURPOSE: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise meth...
Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Aug 8, 2024
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...
Case-Control Studies
Hemodynamics
Deep Learning
Aortic Valve
Predictive Value of Tests
Aged
Young Adult
Adult
Male
Middle Aged
Aorta
Perfusion Imaging
Regional Blood Flow
Image Interpretation, Computer-Assisted
Bicuspid Aortic Valve Disease
Datasets as Topic
Blood Flow Velocity
Humans
Neural Networks, Computer
Female
Reproducibility of Results
Combining Image Similarity and Predictive Artificial Intelligence Models to Decrease Subjectivity in Thyroid Nodule Diagnosis and Improve Malignancy Prediction.
Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
Aug 8, 2024
OBJECTIVES: To evaluate the efficacy of combining predictive artificial intelligence (AI) and image similarity model to risk stratify thyroid nodules, using retrospective external validation study.
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