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Diabetes Mellitus combined with Mild Cognitive Impairment (DM-MCI) is a high incidence disease among the elderly. Patients with DM-MCI have considerably higher risk of dementia, whose daily self-care and life management (i.e.

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Preserving the ability to vividly recall emotionally rich experiences contributes to quality of life in older adulthood. While prior works suggest that moderate-intensity physical activity (MPA) may bolster memory, it is unclear whether this extends to emotionally salient memories consolidated during sleep. In the current study, older adults (mean age = 72.

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Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.

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Body composition abnormalities are prognostic markers in several types of cancer, including colorectal cancer (CRC). Using our data distribution on body composition assessments and classifications could improve clinical evaluations and support population-specific opportune interventions. This study aimed to evaluate the distribution of body composition from computed tomography and assess the associations with overall survival among patients with CRC.

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Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.

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