AIMC Topic: Retrospective Studies
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A deep learning pipeline for systematic and accurate vertebral fracture reporting in computed tomography.
Clinical radiology
Jan 25, 2025
AIM: Spine fractures are a frequent and relevant diagnosis, but systematic documentation is time-consuming and sometimes overlooked. A deep learning pipeline for opportunistic fracture detection in computed tomography (CT) spine images of varying fie...
Machine-learning model based on ultrasomics for non-invasive evaluation of fibrosis in IgA nephropathy.
European radiology
Jan 24, 2025
OBJECTIVES: To develop and validate an ultrasomics-based machine-learning (ML) model for non-invasive assessment of interstitial fibrosis and tubular atrophy (IF/TA) in patients with IgA nephropathy (IgAN).
Development of a Clinically Applicable Deep Learning System Based on Sparse Training Data to Accurately Detect Acute Intracranial Hemorrhage from Non-enhanced Head Computed Tomography.
Neurologia medico-chirurgica
Jan 24, 2025
Non-enhanced head computed tomography is widely used for patients presenting with head trauma or stroke, given acute intracranial hemorrhage significantly influences clinical decision-making. This study aimed to develop a deep learning algorithm, ref...
Detecting B-cell lymphoma-6 overexpression status in primary central nervous system lymphoma using multiparametric MRI-based machine learning.
Neuroradiology
Jan 24, 2025
PURPOSE: In primary central nervous system lymphoma (PCNSL), B-cell lymphoma-6 (BCL-6) is an unfavorable prognostic biomarker. We aim to non-invasively detect BCL-6 overexpression in PCNSL patients using multiparametric MRI and machine learning techn...
Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.
Respiratory research
Jan 24, 2025
BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapidly evolving interstitial lung disease (ILD), driving its mortality. Specific imaging-based biomarkers associated with the evolution of lung disease are need...
AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study.
Journal of medical Internet research
Jan 24, 2025
BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection...
Breast radiation therapy fluence painting with multi-agent deep reinforcement learning.
Medical physics
Jan 23, 2025
BACKGROUND: The electronic compensation (ECOMP) technique for breast radiation therapy provides excellent dose conformity and homogeneity. However, the manual fluence painting process presents a challenge for efficient clinical operation.
Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning.
European radiology
Jan 23, 2025
OBJECTIVES: To assess glymphatic function and white matter integrity in children with autism spectrum disorder (ASD) using multi-parametric MRI, combined with machine learning to evaluate ASD detection performance.
Machine learning prediction of in-hospital mortality and external validation in patients with cardiogenic shock: the RESCUE score.
Revista espanola de cardiologia (English ed.)
Jan 22, 2025
INTRODUCTION AND OBJECTIVES: Despite advances in mechanical circulatory support, mortality rates in cardiogenic shock (CS) remain high. A reliable risk stratification system could serve as a valuable guide in the clinical management of patients with ...
CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.
Abdominal radiology (New York)
Jan 22, 2025
BACKGROUND: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced ...
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