AIMC Topic: Aged, 80 and over
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Predicting mortality risk in Alzheimer's disease using machine learning based on lifestyle and physical activity.
Scientific reports
Jul 24, 2025
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...
Development and temporal validation of a nomogram for predicting ICU 28-day mortality in middle-aged and elderly sepsis patients: An eICU database study.
PloS one
Jul 21, 2025
BACKGROUND AND OBJECTIVE: Despite advances in intensive care, sepsis remains a leading cause of mortality in intensive care unit (ICU) patients, especially middle-aged and elderly individuals. Given the limitations of conventional scoring systems and...
Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device.
Scientific reports
Jul 20, 2025
Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarker, but trad...
Deep learning to identify stroke within 4.5 h using DWI and FLAIR in a prospective multicenter study.
Scientific reports
Jul 19, 2025
To enhance thrombolysis eligibility in acute ischemic stroke, we developed a deep learning model to estimate stroke onset within 4.5 h using diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) images. Given the variabilit...
Visualized load-bearing-based robot control system improves early function in femoral neck fracture patients: a randomized controlled trial focusing on outcomes after total hip arthroplasty.
Journal of orthopaedic surgery and research
Jul 18, 2025
BACKGROUND: After total hip arthroplasty (THA), standing and walking balance are greatly affected in the early recovery period, making it important to increase weight-bearing amount (WBA) on the surgical side. Sometimes, traditional treatment methods...
Type of pre-existing chronic conditions and their associations with Merkel cell carcinoma (MCC) treatment: Prediction and interpretation using machine learning methods.
PloS one
Jul 18, 2025
OBJECTIVE: This study examined the prevalence of pre-existing chronic conditions and their association with the receipt of specific cancer-directed treatments among older adults with incident primary Merkel Cell Carcinoma (MCC) using novel predictive...
Opportunistic computed tomography (CT) assessment of osteoporosis in patients undergoing transcatheter aortic valve replacement (TAVR).
Archives of osteoporosis
Jul 17, 2025
UNLABELLED: CT-based opportunistic screening using artificial intelligence finds a high prevalence (43%) of osteoporosis in CT scans obtained for planning of transcatheter aortic valve replacement. Thus, opportunistic screening may be a cost-effectiv...
Conditional GAN performs better than orthopedic surgeon in virtual reduction of femoral neck fracture.
BMC musculoskeletal disorders
Jul 16, 2025
OBJECTIVE: Satisfied reduction of fracture is hard to achieve. The purpose of this study is to develop a virtual fracture reduction technique using conditional GAN (Generative Adversarial Network), and evaluate its performance in simulating and guidi...
Developing an explainable machine learning and fog computing-based visual rating scale for the prediction of dementia progression.
Scientific reports
Jul 16, 2025
Recently, dementia research has primarily concentrated on using Magnetic Resonance Imaging (MRI) to develop learning models in processing and analyzing brain data. However, these models often cannot provide early detection of affected brain regions. ...
Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.
Scientific reports
Jul 15, 2025
Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. This c...
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