AIMC Topic: Aged, 80 and over

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Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.

Computers in biology and medicine Mar 5, 2025
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
Predictive Learning Models Psychological Well-Being United States Department of Veterans Affairs Veterans United States Department of Defense Humans Suicide, Completed Adolescent Electronic Health Records Suicide Prevention United States Natural Language Processing Adult Female Male Aged Middle Aged Aged, 80 and over Risk Assessment Young Adult Case-Control Studies
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Machine learning-based classification of spatially resolved diffuse reflectance and autofluorescence spectra acquired on human skin for actinic keratoses and skin carcinoma diagnostics aid.

Journal of biomedical optics Mar 4, 2025
SIGNIFICANCE: The incidence of keratinocyte carcinomas (KCs) is increasing every year, making the task of developing new methods for KC early diagnosis of utmost medical and economical importance.
Humans Machine Learning Keratosis, Actinic Female Skin Neoplasms Support Vector Machine Carcinoma, Basal Cell Spectrometry, Fluorescence Carcinoma, Squamous Cell Discriminant Analysis Aged Aged, 80 and over Skin Male Optical Imaging Middle Aged Diagnosis, Computer-Assisted
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CT Differentiation and Prognostic Modeling in COVID-19 and Influenza A Pneumonia.

Academic radiology Mar 3, 2025
RATIONALE AND OBJECTIVES: This study aimed to compare CT features of COVID-19 and Influenza A pneumonia, develop a diagnostic differential model, and explore a prognostic model for lesion resolution.
Retrospective Studies Tomography, X-Ray Computed Female SARS-CoV-2 Aged Humans Machine Learning COVID-19 Prognosis Lung Influenza A virus Nomograms Diagnosis, Differential Aged, 80 and over Influenza, Human Adult Male Middle Aged
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Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair.

Journal of the American Heart Association Mar 3, 2025
BACKGROUND: Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EVAR) are complex procedures that carry a significant risk of complications. While risk prediction tools can aid in clinical decision making, they remai...
Aged, 80 and over Male Risk Assessment Postoperative Complications Treatment Outcome Retrospective Studies Female Risk Factors Aged Predictive Value of Tests Aortic Aneurysm, Thoracic Blood Vessel Prosthesis Implantation Endovascular Procedures Humans Machine Learning Databases, Factual
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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...
Depression Wearable Electronic Devices Feasibility Studies Aged, 80 and over Male Quality of Life Exercise Humans Machine Learning Female Aged
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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...
Aged Aged, 80 and over Male Proteomics Alzheimer Disease Hydrocephalus, Normal Pressure Humans Machine Learning Biomarkers Female
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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...
Humans Machine Learning Middle Aged Prognosis Support Vector Machine Female Aged Ischemic Stroke Aged, 80 and over Diffusion Magnetic Resonance Imaging Radiomics Male
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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...
Humans Machine Learning Female Aged Aged, 80 and over Obesity Sarcopenia Male China ROC Curve Support Vector Machine
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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...
Female Humans Aged Treatment Outcome Artificial Intelligence Aged, 80 and over Aortic Valve Stenosis Retrospective Studies Male Aorta, Thoracic Femoral Artery Transcatheter Aortic Valve Replacement
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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...
Male Middle Aged Aged Humans Deep Learning Aged, 80 and over Schizophrenia Brain Magnetic Resonance Imaging Precision Medicine Young Adult Female Adult
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