BACKGROUND: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from ...
BACKGROUND: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variati...
PURPOSE: Distinguishing between Osteonecrosis of the femoral head (ONFH) and Osteoarthritis (OA) can be subjective and vary between users with different backgrounds and expertise. This study aimed to construct and evaluate several Radiomics-based mac...
BACKGROUND: Amphibians are experiencing substantial declines attributed to emerging pathogens. Efforts to understand what drives patterns of pathogen prevalence and differential responses among species are challenging because numerous factors related...
International journal of oral and maxillofacial surgery
Jan 28, 2025
With developments in computer science and technology, great progress has been made in three-dimensional (3D) ultrasound. Recently, ultrasound-based 3D bone modelling has attracted much attention, and its accuracy has been studied for the femur, tibia...
OBJECTIVE: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based ite...
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Jan 28, 2025
OBJECTIVES: This study aimed to evaluate the anthropometric accuracy of 3D face reconstruction based on neural networks (3DFRBN) using 2D images, including the assessment of global errors and landmarks, as well as linear and angular measurements.
BACKGROUND: This study aimed to develop a dynamic survival prediction model utilizing conditional survival (CS) analysis and machine learning techniques for gastric neuroendocrine carcinomas (GNECs).
OBJECTIVE: To assess the utility and challenges of using natural language processing (NLP) in electronic health records (EHRs) to ascertain health-related social needs (HRSNs) among older adults.
BACKGROUND: The heterogeneity of breast cancer (BC) necessitates the identification of novel subtypes and prognostic models to enhance patient stratification and treatment strategies. This study aims to identify novel BC subtypes based on PANoptosis-...
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