AIMC Topic: Aged, 80 and over

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Multimodal Visualization and Explainable Machine Learning-Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study.

Journal of medical Internet research May 1, 2025
BACKGROUND: Currently, there is a paucity of literature addressing personalized risk stratification using multimodal data in patients with symptomatic aortic stenosis and heart failure with preserved ejection fraction (HFpEF) following transcatheter ...
Transcatheter Aortic Valve Replacement Risk Assessment Cohort Studies Aortic Valve Stenosis Heart Failure Humans Machine Learning Biomarkers Prognosis Female Aged Aged, 80 and over Male Stroke Volume
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Detection of Pulmonary Nodules on Ultra-low Dose Chest Computed Tomography With Deep-learning Image Reconstruction Algorithm.

Journal of thoracic imaging May 1, 2025
PURPOSE: To evaluate the accuracy of ultra-low dose (ULD) chest computed tomography (CT), with a radiation exposure equivalent to a 2-view chest x-ray, for pulmonary nodule detection using deep learning image reconstruction (DLIR).
Humans Algorithms Prospective Studies Tomography, X-Ray Computed Cross-Sectional Studies Male Middle Aged Lung Deep Learning Female Aged Aged, 80 and over Adult Sensitivity and Specificity Radiation Dosage Lung Neoplasms Radiography, Thoracic Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted
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Factors influencing short-term and long-term survival rates in stroke patients receiving enteral nutrition: a machine learning approach using MIMIC-IV database.

BMC neurology Apr 30, 2025
PURPOSE: This study aims to evaluate the survival and mortality rates of stroke patients after receiving enteral nutrition, and to explore factors influencing long-term survival. With an aging society, nutritional management of stroke patients has be...
Middle Aged Stroke Kaplan-Meier Estimate Enteral Nutrition Aged Humans Aged, 80 and over Machine Learning Survival Rate Databases, Factual Male Female
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Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.

JMIR aging Apr 30, 2025
BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. T...
East Asian People Longevity Humans Aged, 80 and over Machine Learning Male Prospective Studies China Biomarkers Cognitive Dysfunction Female Longitudinal Studies Aged
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Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

European journal of radiology Apr 29, 2025
This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 R...
Carcinoma, Renal Cell Boosting Machine Learning Algorithms Contrast Media Female Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Kidney Neoplasms Aged Aged, 80 and over Adult Sensitivity and Specificity Radiomics Humans Male Machine Learning Middle Aged Tomography, X-Ray Computed
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A machine learning tool for prediction of vertebral compression fracture following stereotactic body radiation therapy for spinal metastases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Apr 29, 2025
BACKGROUND AND PURPOSE: The most common adverse event following spine stereotactic body radiotherapy (SBRT) is vertebral compression fracture (VCF). There is interest in the development of patient-specific tools that can predict those at high risk of...
Humans Machine Learning Retrospective Studies Middle Aged Spinal Neoplasms Radiosurgery Spinal Fractures Fractures, Compression Female Risk Factors Aged Aged, 80 and over Male
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Automated radiography assessment of ankle joint instability using deep learning.

Scientific reports Apr 29, 2025
This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system...
Middle Aged Deep Learning Adolescent Child Radiography Ankle Joint Joint Instability Aged Aged, 80 and over Young Adult Adult Male Humans Female
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Intraocular lens calculation formula developed using artificial intelligence for ultrasonic biometry.

Arquivos brasileiros de oftalmologia Apr 28, 2025
PURPOSE: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. This endeavor is aimed at enhancing precision and efficacy in the selection of intraocular lenses, par...
Refraction, Ocular Aged Humans Lens Implantation, Intraocular Aged, 80 and over Artificial Intelligence Lenses, Intraocular Adult Phacoemulsification Female Male Biometry Reproducibility of Results Middle Aged
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Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.

BMJ open Apr 27, 2025
OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates and limited prediction tools. Despite advances in resuscitation, predicting 30-day survival remains difficult, and current methods lack interpretabilit...
Humans Machine Learning Registries Cardiopulmonary Resuscitation Survival Rate Female Heart Arrest Male Sweden Middle Aged Aged Cohort Studies Aged, 80 and over ROC Curve
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Machine learning for predicting medical outcomes associated with acute lithium poisoning.

Scientific reports Apr 25, 2025
The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predicting medical outcomes. This study aimed to evaluate the effectiveness of the random forest algorithm ...
Infant Adolescent Humans Young Adult Lithium Machine Learning Adult Child, Preschool Algorithms Male Child Female Middle Aged Infant, Newborn Aged Aged, 80 and over
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