BACKGROUND: Major bleeding is a severe complication in critically ill medical patients, resulting in significant morbidity, mortality, and healthcare costs. This study aims to assess the incidence and risk factors for major bleeding in hospitalised m...
Oral surgery, oral medicine, oral pathology and oral radiology
Mar 29, 2025
OBJECTIVE: Accurate preoperative diagnosis is essential for selecting appropriate surgical interventions. This study aims to develop a deep learning model based on ultrasound (US) imaging to accurately differentiate between benign and malignant saliv...
RATIONALE AND OBJECTIVES: Ultrasound (US)-based deep learning (DL) models for grading the severity of carpal tunnel syndrome (CTS) are scarce. We aimed to advance CTS grading by developing a joint-DL model integrating clinical information and multimo...
OBJECTIVE: This study aimed to develop and validate a nomogram combining F-FDG PET radiomics and clinical factors to non-invasively predict bone marrow involvement (BMI) in patients with lymphoma.
Exploring the clinical significance of employing deep learning methodologies on ultrasound images for the development of an automated model to accurately identify pleomorphic adenomas and Warthin tumors in salivary glands. A retrospective study was c...
PURPOSE: This study aimed to measure the impact of a community-based lifestyle modification intervention program on the Health-Related Quality of Life (HRQoL) of adults with prediabetes in two Latin American cities.
In recent years, machine learning-based handwriting analysis has emerged as a valuable tool for supporting the early diagnosis of Alzheimer's disease and predicting its progression. Traditional approaches represent handwriting tasks using a single fe...
This paper introduces a novel convolutional neural network model with an attention mechanism to advance Alzheimer disease (AD) classification using Magnetic Resonance Imaging (MRI). The model architecture is meticulously crafted to enhance feature ex...
BACKGROUND: Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk fac...
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