AIMC Topic: Aged
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Associations between the 24-h Activity Daily Cycle and Incident Dementia.
Medicine and science in sports and exercise
May 5, 2025
BACKGROUND: Physical activity, sedentary behavior (SB), and sleep all impact the risk of incident dementia, however, engagement in these activities is constrained by the 24-h day. Increasing time spent in one activity necessarily reduces time spent i...
Prediction of EGFR Mutations in Lung Adenocarcinoma via CT Images: A Comparative Study of Intratumoral and Peritumoral Radiomics, Deep Learning, and Fusion Models.
Academic radiology
May 5, 2025
RATIONALE AND OBJECTIVES: This study aims to analyze the intratumoral and peritumoral characteristics of lung adenocarcinoma patients on the basis of chest CT images via radiomic and deep learning methods and to develop and validate a multimodel fusi...
Optimizing elderly care: A data-driven AI model for predicting polypharmacy risk in the elderly using SHARE data.
Neuroscience
May 5, 2025
BACKGROUND: Aging is frequently accompanied by multimorbidity, the presence of multiple chronic conditions, which contributes to declines in both cognitive and physical function and presents complex health challenges. One such challenge is Polypharma...
Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study.
Journal of medical Internet research
May 5, 2025
BACKGROUND: Systemically identifying caregivers in the electronic health record (EHR) is a critical step for delivering patient-centered care, enhancing care coordination, and advancing research and population health efforts in caregiving. Despite EH...
Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence.
JCO precision oncology
May 5, 2025
PURPOSE: Endometrial cancer (EC) is the most common gynecologic cancer in the United States with rising incidence and mortality. Despite optimal treatment, 15%-20% of all patients will recur. To better select patients for adjuvant therapy, it is impo...
Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.
American journal of Alzheimer's disease and other dementias
May 5, 2025
To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). A recursive partitioning tree model was developed using ARMADA data and the NIH Toolbox, a...
Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 5, 2025
For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). In order to effectively identify the most significant biomarkers associated w...
Use of posterior probabilities from a long short-term memory network for characterizing dance behavior with multiple accelerometers.
Journal of Alzheimer's disease : JAD
May 4, 2025
BackgroundDancing may be protective for cognitive health among adults with mild cognitive impairment, Alzheimer's disease or dementia; however, additional methods are needed to characterize motor behavior quality in studies of dance.ObjectiveTo deter...
Thorax-encompassing multi-modality PET/CT deep learning model for resected lung cancer prognostication: A retrospective, multicenter study.
Medical physics
May 3, 2025
BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery as their primary form of treatment. However, studies have shown that a high proportion of these patients will experience a recurrence after their resec...
Explainable machine learning model for prediction of 28-day all-cause mortality in immunocompromised patients in the intensive care unit: a retrospective cohort study based on MIMIC-IV database.
European journal of medical research
May 3, 2025
OBJECTIVES: This study aimed to develop and validate an explainable machine learning (ML) model to predict 28-day all-cause mortality in immunocompromised patients admitted to the intensive care unit (ICU). Accurate and interpretable mortality predic...
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