AIMC Topic: Aged

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Radiomics of PET Using Neural Networks for Prediction of Alzheimer's Disease Diagnosis.

Statistics in medicine
Positron emission tomography (PET) imaging technology is widely used for diagnosing Alzheimer's disease (AD) in people with dementia. Although various computational methods have been proposed for diagnosis of AD using PET images, prediction of diseas...

Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.

Clinical transplantation
INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as infection, increased length of stay, and increased patient mortality. Abdominal computed tomography...

Machine Learning Insights Into Amputation Risk: Evaluating Wound Classification Systems in Diabetic Foot Ulcers.

International wound journal
This study compares the performance of various wound classification systems to determine which system most effectively predicts amputation risk in diabetic foot ulcer (DFU) patients. Additionally, it identifies the key clinical and socioeconomic fact...

Adaptive Breast MRI Scanning Using AI.

Radiology
Background MRI protocols typically involve many imaging sequences and often require too much time. Purpose To simulate artificial intelligence (AI)-directed stratified scanning for screening breast MRI with various triage thresholds and evaluate its ...

Detection of emergency department patients at risk of dementia through artificial intelligence.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The study aimed to develop and validate the Emergency Department Dementia Algorithm (EDDA) to detect dementia among older adults (65+) and support clinical decision-making in the emergency department (ED).

Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia.

Critical care explorations
OBJECTIVES: Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, vasopressors, and renal replacement therapy (RRT). This study aimed to develop a machine learning (ML) model that predicts the need for such interventi...

Identification and validation of inflammatory response genes linking chronic kidney disease with coronary artery disease based on bioinformatics and machine learning.

Scientific reports
Coronary artery disease (CAD) commonly occurs and elevates the risk of cardiovascular events and mortality in chronic kidney disease (CKD) patients. The underlying pathogenesis of CKD-related CAD is believed to be closely linked to inflammatory respo...

Predicting long-term patency of radiocephalic arteriovenous fistulas with machine learning and the PREDICT-AVF web app.

Scientific reports
The goal of this study was to expand our previously created prediction tool (PREDICT-AVF) and web app by estimating long-term primary and secondary patency of radiocephalic AVFs. The data source was 911 patients from PATENCY-1 and PATENCY-2 randomize...