CONTEXT: Staging cancer patients is crucial and requires analyzing all removed lymph nodes microscopically for metastasis. For this pivotal task, convolutional neural networks (CNN) can reduce workload and improve diagnostic accuracy.
AIM: To develop and validate a magnetic resonance imaging (MRI)-based deep learning radiomics model (DLRM) to predict recurrence-free survival (RFS) in lung cancer patients after surgical resection of brain metastases (BrMs).
AIMS: This study assessed the diagnostic accuracy and prognostic implications of an artificial intelligence (AI) tool for coronary artery calcification (CAC) assessment on nongated, noncontrast thoracic computed tomography (CT).
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jun 1, 2025
OBJECTIVE: This study aims to develop a deep learning model for a robust diagnosis of Carpal Tunnel Syndrome (CTS) based on comparative classification leveraging the ultrasound images of the thenar and hypothenar muscles.
Liver international : official journal of the International Association for the Study of the Liver
Jun 1, 2025
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is linked to cognitive decline and dementia risk. We aimed to investigate the association between MASLD and brain ageing and explore the role of low-grade inflammation.
Journal of the Association for Research in Otolaryngology : JARO
Jun 1, 2025
OBJECTIVE: Differentiating between Meniere's disease (MD) and vestibular migraine (VM) is challenging due to overlapping symptoms and limited diagnostic tools. Traditional statistical methods often rely on physician judgment and struggle with complex...
INTRODUCTION: Current decision support tools designed to predict postoperative complications, following cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC), are limited by small sample sizes and lack of external validatio...
Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and intervention. However, traditional survey tools such as DASS-42 are time-consuming in responding and scoring. We used a novel advanced machine learning approach...
BACKGROUND: The PRECISE framework, defined as Patient-Focused Radiology Reports with Enhanced Clarity and Informative Summaries for Effective Communication, leverages GPT-4 to create patient-friendly summaries of radiology reports at a sixth-grade re...
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