Annals of agricultural and environmental medicine : AAEM
Jul 8, 2024
INTRODUCTION AND OBJECTIVE: Surface electromyography (sEMG) measurements are a valid method for sublesional muscle activity following spinal cord injury (SCI). In the literature there are few reports evaluating the effect of robotic assisted gait tra...
International journal of oral and maxillofacial surgery
Jul 8, 2024
Although rare overall, salivary gland carcinomas (SGCs) are among the most common oral and maxillofacial malignancies. The aim of this study was to develop a machine learning-based model to predict the survival of patients with SGC. Patients in whom ...
BACKGROUND: Abdominal aortic aneurysm (AAA) poses a significant health risk and is influenced by various compositional features. This study aimed to develop an artificial intelligence-driven multiomics predictive model for AAA subtypes to identify he...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 8, 2024
PURPOSE: To evaluate lymphovascular invasion (LVI) in breast cancer by comparing the diagnostic performance of preoperative multimodal magnetic resonance imaging (MRI)-based radiomics and deep-learning (DL) models.
Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many cancers are missed. Supplemental screening using magnetic resonance imaging (MRI) can reduce the numbe...
BACKGROUND: Predicting the accurate preoperative staging of bladder cancer (BLCA), which markedly affects treatment decisions and patient outcomes, using traditional clinical parameters is challenging. Nevertheless, emerging studies in radiomics, esp...
Hyperuricemia (HUA) has emerged as the second most prevalent metabolic disorder characterized by prolonged and asymptomatic period, triggering gout and metabolism-related outcomes. Early detection and prognosis prediction for HUA and gout are crucial...
PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nu...
OBJECTIVE: Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test a magnetic resonance imaging (MRI)-based joint space (JS) radiomic model (RM) to predict radiographic...
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