Journal of cachexia, sarcopenia and muscle
Jun 1, 2025
BACKGROUND: Muscle strength is one of the key components in the diagnosis of sarcopenia. The aim of this study was to train a machine learning model to predict reference values and percentiles for handgrip strength and chair-stand test (CST), in a la...
Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology
Jun 1, 2025
OBJECTIVES: This study aimed to construct a risk prediction model for the occurrence of the demora-lization syndrome in patients with oral cancer and provide a scientific basis for the prevention of this syndrome in patients with oral cancer and the ...
BACKGROUND: Cognitive impairment is common but frequently undiagnosed in the dialysis population. We aimed to develop and validate a quick and accurate screening tool using machine-learning-based approaches in them.
Colorectal cancer (CRC) remains a major cause of cancer-related deaths worldwide, with early detection being crucial for improving survival rates. Despite the potential of extracellular vesicles (EVs) as blood biomarkers for CRC diagnosis, their clin...
BACKGROUND: The phantom sound of tinnitus can be an extremely debilitating condition. The thalamocortical dysrhythmia (TCD) hypothesis is a feature of subjective tinnitus; however, its consistency in characterizing different types of tinnitus remains...
OBJECTIVE: Evaluating leukoaraiosis (LA) on CT is challenging due to its low contrast and similarity to parenchymal gliosis. We developed and validated a deep learning algorithm for LA segmentation using CT-MRIFLAIR paired data from a multicenter Kor...
OBJECTIVE: Stroke is a leading cause of morbidity and disability worldwide. Post-stroke cognitive impairment (PSCI) significantly affects long-term prognosis in acute anterior circulation large-vessel occlusion stroke (LVO-AIS). This study aims to de...
"Predicted brain age" refers to a biomarker of structural brain health derived from machine learning analysis of T1-weighted brain magnetic resonance (MR) images. A range of machine learning methods have been used to predict brain age, with convoluti...
The brain undergoes complex but normal structural changes during the aging process in healthy adults, whereas deviations from the normal aging patterns of the brain can be indicative of various conditions as well as an increased risk for the developm...
Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstanding performance. Nevertheless, deep learning remains a black box as it is hard to interpret which bra...
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