AIMC Topic: Retrospective Studies
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A Novel Visual Model for Predicting Prognosis of Resected Hepatoblastoma: A Multicenter Study.
Academic radiology
Mar 26, 2025
RATIONALE AND OBJECTIVES: This study aimed to evaluate the application of a contrast-enhanced CT-based visual model in predicting postoperative prognosis in patients with hepatoblastoma (HB).
Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.
JACC. Cardiovascular imaging
Mar 26, 2025
BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically.
Predictive Value of Tests
Sex Factors
Aortic Valve Insufficiency
Magnetic Resonance Imaging, Cine
Humans
Severity of Illness Index
Time Factors
Machine Learning
United States
Decision Support Techniques
Aortic Valve
Reproducibility of Results
Unsupervised Machine Learning
Risk Factors
Ventricular Function, Left
Aged
Middle Aged
Adult
Risk Assessment
Phenotype
Male
Disease Progression
Prognosis
Retrospective Studies
Female
Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score.
Critical care explorations
Mar 26, 2025
BACKGROUND: Early detection of clinical deterioration using machine-learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not t...
Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.
Medicina (Kaunas, Lithuania)
Mar 26, 2025
: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This stud...
Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.
BMC infectious diseases
Mar 26, 2025
OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematologic malignancies(HMs), particularly amid rising antibiotic resistance. This study aimed to analyze pathogen distribution, drug-resistance patterns and...
Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery.
BMC medical imaging
Mar 26, 2025
BACKGROUND AND PURPOSE: Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several DL algorithms focu...
Preliminary evaluation of ChatGPT model iterations in emergency department diagnostics.
Scientific reports
Mar 26, 2025
Large language model chatbots such as ChatGPT have shown the potential in assisting health professionals in emergency departments (EDs). However, the diagnostic accuracy of newer ChatGPT models remains unclear. This retrospective study evaluated the ...
AI-powered model for predicting mortality risk in VA-ECMO patients: a multicenter cohort study.
Scientific reports
Mar 26, 2025
Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a critical life support technology for severely ill patients. Despite its benefits, patients face high costs and significant mortality risks. To improve clinical decision-making, this stu...
Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI.
European radiology
Mar 25, 2025
OBJECTIVE: To investigate whether digital mammography (DM) with artificial intelligence-based computer-aided diagnosis (AI-CAD) predicts pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in human epidermal growth factor receptor...
Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohort.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 25, 2025
PURPOSE: Information on deep learning (DL) tumor segmentation accuracy on a voxel and a structure level is essential for clinical introduction. In a previous study, a DL model was developed for oropharyngeal cancer (OPC) primary tumor (PT) segmentati...
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