AIMC Topic: Predictive Value of Tests

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Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.

European respiratory review : an official journal of the European Respiratory Society Nov 13, 2024
BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) offers the potential for enhanced prediction models.
Humans Predictive Value of Tests Hospitalization Adolescent Machine Learning Emergency Service, Hospital Asthma Decision Support Techniques Child, Preschool Male Patient Admission Prognosis Risk Assessment Child Female Disease Progression Age Factors Risk Factors
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Predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma: nomograms based on deep learning analysis of gadoxetic acid-enhanced MRI.

European radiology Nov 12, 2024
OBJECTIVES: This study aimed to develop nomograms for predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC), using deep learning analysis of Gadoxetic acid-enhanced hepatobiliary (HBP) MRI.
Liver Failure Gadolinium DTPA Postoperative Complications Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Nomograms Contrast Media Magnetic Resonance Imaging Predictive Value of Tests Hepatectomy Retrospective Studies Female Aged Humans Male Middle Aged
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A Novel Machine Learning-based Predictive Model of Clinically Significant Prostate Cancer and Online Risk Calculator.

Urology Nov 12, 2024
OBJECTIVE: To create a machine-learning predictive model combining prostate imaging-reporting and data system (PI-RADS) score, PSA density, and clinical variables to predict clinically significant prostate cancer (csPCa).
Male Middle Aged Risk Assessment Predictive Value of Tests Prostatic Neoplasms Prostate-Specific Antigen Prostate Humans Machine Learning Retrospective Studies Aged
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Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.

Genes Nov 12, 2024
Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. The anoikis-related prognostic signature (ANRS) was gene...
Transcriptome Real-Time Polymerase Chain Reaction Reverse Transcriptase Polymerase Chain Reaction Immunotherapy Enzyme-Linked Immunosorbent Assay Treatment Outcome Databases, Genetic Predictive Value of Tests Drug Screening Assays, Antitumor Tumor Microenvironment Biomarkers, Tumor Female Middle Aged Anoikis Reproducibility of Results Antineoplastic Agents Machine Learning Aged Gene Expression Profiling Gene Expression Prognosis Breast Neoplasms Blotting, Western Imatinib Mesylate Proportional Hazards Models
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Diagnostic and predictive value of radiomics-based machine learning for intracranial aneurysm rupture status: a systematic review and meta-analysis.

Neurosurgical review Nov 12, 2024
Currently, the growing interest in radiomics within the clinical practice has prompted some researchers to differentiate the rupture status of intracranial aneurysm (IA) by developing radiomics-based machine learning models. However, systematic evide...
Predictive Value of Tests Aneurysm, Ruptured Intracranial Aneurysm Humans Machine Learning Radiomics
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Assessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography.

The international journal of cardiovascular imaging Nov 8, 2024
PURPOSE: This study aimed to evaluate the efficacy of the Chat Generative Pre-trained Transformer (ChatGPT) in guiding the need for invasive coronary angiography (ICA) in high-risk non-ST-elevation (NSTE) acute coronary syndrome (ACS) patients based ...
Humans Artificial Intelligence Decision Support Techniques Prospective Studies Predictive Value of Tests Double-Blind Method Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Acute Coronary Syndrome Computed Tomography Angiography Aged Male Middle Aged Risk Assessment Non-ST Elevated Myocardial Infarction Clinical Decision-Making Female Reproducibility of Results Risk Factors
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Development and accuracy of an artificial intelligence model for predicting the progression of hip osteoarthritis using plain radiographs and clinical data: a retrospective study.

BMC musculoskeletal disorders Nov 8, 2024
BACKGROUND: Predicting the progression of hip osteoarthritis (OA) remains challenging, and no reliable predictive method has been established. This study aimed to develop an artificial intelligence (AI) model to predict hip OA progression via plain r...
Retrospective Studies Female Aged Male Middle Aged Humans Artificial Intelligence Osteoarthritis, Hip Disease Progression Predictive Value of Tests Radiography Hip Joint Arthroplasty, Replacement, Hip
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The performance of machine learning for predicting the recurrent stroke: a systematic review and meta-analysis on 24,350 patients.

Acta neurologica Belgica Nov 7, 2024
BACKGROUND: Stroke is a leading cause of death and disability worldwide. Approximately one-third of patients with stroke experienced a second stroke. This study investigates the predictive value of machine learning (ML) algorithms for recurrent strok...
Humans Machine Learning Predictive Value of Tests Stroke Recurrence
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Joint suppression of cardiac bSSFP cine banding and flow artifacts using twofold phase-cycling and a dual-encoder neural network.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Nov 7, 2024
BACKGROUND: Cardiac balanced steady state free precession (bSSFP) cine imaging suffers from banding and flow artifacts induced by off-resonance. The work aimed to develop a twofold phase cycling sequence with a neural network-based reconstruction (2P...
Ventricular Function, Left Middle Aged Case-Control Studies Predictive Value of Tests Image Interpretation, Computer-Assisted Artifacts Magnetic Resonance Imaging, Cine Humans Reproducibility of Results Neural Networks, Computer Aged Prospective Studies Young Adult Female Adult Male
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Deep learning automatically distinguishes myocarditis patients from normal subjects based on MRI.

The international journal of cardiovascular imaging Nov 7, 2024
Myocarditis, characterized by inflammation of the myocardial tissue, presents substantial risks to cardiovascular functionality, potentially precipitating critical outcomes including heart failure and arrhythmias. This investigation primarily aims to...
Middle Aged Case-Control Studies Deep Learning Magnetic Resonance Imaging Predictive Value of Tests Reproducibility of Results Young Adult Adult Male Myocardium Myocarditis Image Interpretation, Computer-Assisted Automation Humans Magnetic Resonance Imaging, Cine Retrospective Studies Female
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