AIMC Topic: Aged

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Prediction Model of Intradialytic Hypertension in Hemodialysis Patients Based on Machine Learning.

Journal of medical systems
The escalating global burden of chronic kidney disease (CKD), particularly end-stage renal disease (ESRD), has intensified reliance on hemodialysis (HD), imposing substantial financial and operational burdens on healthcare systems and patients. Intra...

Plasma Proteomic High-Performance Biomarkers for Early Diagnosis of Colorectal Cancer.

Journal of proteome research
Colorectal cancer (CRC) is a major global health challenge due to its high incidence, mortality, and low rate of early detection. Early diagnosis, targeting precancerous lesions (advanced adenomas) and early stage CRC (Tis and T1), is critical for im...

Differential modulation of movement speed with state-dependent deep brain stimulation in Parkinson's disease.

Science advances
Subthalamic deep brain stimulation (STN-DBS) provides unprecedented spatiotemporal precision for the treatment of Parkinson's disease (PD), allowing for direct real-time state-specific adjustments. Inspired by findings from optogenetic stimulation in...

Biological Age Estimation From the Age Gap Using Deep Learning Integrating Morbidity and Mortality: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Biological age (BA) is increasingly recognized as a valuable alternative to chronological age (CA) for assessing an individual's health and aging status. However, existing models are based on limited clinical parameters and have not thoro...

Exploring Women's Perceptions of Traditional Mammography and the Concept of AI-Driven Thermography to Improve the Breast Cancer Screening Journey: Mixed Methods Study.

JMIR cancer
BACKGROUND: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, rad...

Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach.

JMIR medical informatics
BACKGROUND: Cirrhosis is a leading cause of noncancer deaths in gastrointestinal diseases, resulting in high hospitalization and readmission rates. Early identification of high-risk patients is vital for proactive interventions and improving health c...

Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

PloS one
BACKGROUND: In order to seriously impact the global burden of heart failure (HF) and coronary artery disease (CAD), identifying at-risk individuals as early as possible is vital. Risk calculator tools in wide clinical use today are informed by tradit...

A multiomics recovery factor predicts long COVID in the IMPACC study.

The Journal of clinical investigation
BACKGROUNDFollowing SARS-CoV-2 infection, approximately 10%-35% of patients with COVID-19 experience long COVID (LC), in which debilitating symptoms persist for at least 3 months. Elucidating the biologic underpinnings of LC could identify therapeuti...

Use of artificial intelligence for classification of fractures around the elbow in adults according to the 2018 AO/OTA classification system.

BMC musculoskeletal disorders
BACKGROUND: This study evaluates the accuracy of an Artificial Intelligence (AI) system, specifically a convolutional neural network (CNN), in classifying elbow fractures using the detailed 2018 AO/OTA fracture classification system.

Early Detection of Lung Metastases in Breast Cancer Using YOLOv10 and Transfer Learning: A Diagnostic Accuracy Study.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND This study used CT imaging analyzed with deep learning techniques to assess the diagnostic accuracy of lung metastasis detection in patients with breast cancer. The aim of the research was to create and verify a system for detecting malign...