AIMC Topic: Aged, 80 and over

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Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study.

JMIR aging Mar 3, 2025
BACKGROUND: Depression, characterized by persistent sadness and loss of interest in daily activities, greatly reduces quality of life. Early detection is vital for effective treatment and intervention. While many studies use wearable devices to class...
Wearable Electronic Devices Feasibility Studies Machine Learning Female Aged Aged, 80 and over Male Quality of Life Exercise Depression Humans
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Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer's disease biomarkers.

Fluids and barriers of the CNS Mar 3, 2025
PURPOSE: This study explores the application of machine learning to high-dimensional proteomics datasets for identifying Alzheimer's disease (AD) biomarkers. AD, a neurodegenerative disorder affecting millions worldwide, necessitates early and accura...
Humans Machine Learning Hydrocephalus, Normal Pressure Aged, 80 and over Biomarkers Female Male Aged Proteomics Alzheimer Disease
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Diffusion-Weighted Imaging-Based Radiomics Features and Machine Learning Method to Predict the 90-Day Prognosis in Patients With Acute Ischemic Stroke.

The neurologist Mar 1, 2025
OBJECTIVES: The evaluation of the prognosis of patients with acute ischemic stroke (AIS) is of great significance in clinical practice. We aim to evaluate the feasibility and effectiveness of diffusion-weighted imaging (DWI) image-based radiomics fea...
Prognosis Female Aged Aged, 80 and over Humans Machine Learning Ischemic Stroke Diffusion Magnetic Resonance Imaging Radiomics Male Middle Aged Support Vector Machine
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Development and multi-center cross-setting validation of an explainable prediction model for sarcopenic obesity: a machine learning approach based on readily available clinical features.

Aging clinical and experimental research Mar 1, 2025
OBJECTIVES: Sarcopenic obesity (SO), characterized by the coexistence of obesity and sarcopenia, is an increasingly prevalent condition in aging populations, associated with numerous adverse health outcomes. We aimed to identify and validate an expla...
ROC Curve Support Vector Machine Obesity Humans Sarcopenia Machine Learning Female Aged Aged, 80 and over Male China
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Clinical value of aortic arch morphology in transfemoral TAVR: artificial intelligence evaluation.

International journal of surgery (London, England) Mar 1, 2025
BACKGROUND: The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study w...
Humans Aortic Valve Stenosis Aged Artificial Intelligence Aorta, Thoracic Aged, 80 and over Retrospective Studies Femoral Artery Male Female Transcatheter Aortic Valve Replacement Treatment Outcome
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Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Translational psychiatry Feb 27, 2025
Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and informative, the technical expertise and resources required to develop normative models may not be a...
Female Aged Aged, 80 and over Young Adult Adult Humans Magnetic Resonance Imaging Male Brain Schizophrenia Middle Aged Precision Medicine Deep Learning
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Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

Clinical interventions in aging Feb 27, 2025
BACKGROUND: Hip fractures have become a significant health concern, particularly among super-aged patients, who were at a high risk of postoperative pneumonia due to their frailty and the presence of multiple comorbidities. This study aims to establi...
Hip Fractures Male Risk Assessment Postoperative Complications Incidence Humans Algorithms China Logistic Models Female Neural Networks, Computer Support Vector Machine Risk Factors Machine Learning Pneumonia Aged, 80 and over
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.

BMC geriatrics Feb 26, 2025
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts health care worldwide, particularly among the elderly population. The accurate classification of AD stages is essential for slowing disease progression an...
Magnetic Resonance Imaging Multimodal Imaging Alzheimer Disease Aged, 80 and over Male Disease Progression Deep Learning Brain Female Aged Humans Algorithms
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Linguistic cues for automatic assessment of Alzheimer's disease across languages.

Journal of Alzheimer's disease : JAD Feb 25, 2025
BackgroundMost common forms of dementia, including Alzheimer's disease, are associated with alterations in spoken language.ObjectiveThis study explores the potential of a speech-based machine learning (ML) approach in estimating cognitive impairment,...
Humans Machine Learning Language Female Aged Aged, 80 and over Male Alzheimer Disease Speech Cues Cognitive Dysfunction Linguistics
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Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma.

BMC cancer Feb 25, 2025
OBJECTIVE: We aimed to develop a preoperative clinical radiomics survival prediction model based on the radiomics features via deep learning to provide a reference basis for preoperative assessment and treatment decisions for patients with gallbladde...
Preoperative Period Male Preoperative Care Prognosis Gallbladder Neoplasms Middle Aged Retrospective Studies Deep Learning Tomography, X-Ray Computed Female Aged Humans Aged, 80 and over Adult Radiomics
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