AIMC Topic: Disease Progression

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A comparison of neural networks and regression-based approaches for estimating kidney function in pediatric chronic kidney disease: Practical predictive epidemiology for clinical management of a progressive disease.

Annals of epidemiology Apr 8, 2025
PURPOSE: Clinical management of pediatric chronic kidney disease requires estimation of glomerular filtration rate (eGFR). Currently, eGFR is determined by two endogenous markers measured in blood: serum creatine (SCr) and cystatin C (CysC). Machine ...
Cystatin C Creatinine Creatine Renal Insufficiency, Chronic Glomerular Filtration Rate Kidney Function Tests Regression Analysis Humans Adolescent Neural Networks, Computer Male Child, Preschool Biomarkers Disease Progression Child Female
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Deep Geometric Learning With Monotonicity Constraints for Alzheimer's Disease Progression.

IEEE transactions on neural networks and learning systems Apr 4, 2025
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for clinical diagnosis and treatment. For this, numerous studies have imple...
Humans Neural Networks, Computer Algorithms Brain Deep Learning Magnetic Resonance Imaging Alzheimer Disease Female Aged Male Disease Progression
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Effects of Renal Function on the Multimodal Brain Networks Affecting Mild Cognitive Impairment Converters in End-Stage Renal Disease.

Academic radiology Apr 3, 2025
RATIONALE AND OBJECTIVES: Cognitive decline is common in End-Stage Renal Disease (ESRD) patients, yet its neural mechanisms are poorly understood. This study investigates structural and functional brain network reconfiguration in ESRD patients transi...
Disease Progression Female Cognitive Dysfunction Aged Humans Kidney Failure, Chronic Male Support Vector Machine Brain Middle Aged Magnetic Resonance Imaging
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Identifying progression subphenotypes of Alzheimer's disease from large-scale electronic health records with machine learning.

Journal of biomedical informatics Apr 1, 2025
OBJECTIVE: Identification of clinically meaningful subphenotypes of disease progression can enhance the understanding of disease heterogeneity and underlying pathophysiology. In this study, we propose a machine learning framework to identify subpheno...
Disease Progression Cognitive Dysfunction United States Alzheimer Disease Machine Learning Phenotype Databases, Factual Electronic Health Records Female Aged Aged, 80 and over Male Humans
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Clinical Trial Notifications Triggered by Artificial Intelligence-Detected Cancer Progression: A Randomized Trial.

JAMA network open Apr 1, 2025
IMPORTANCE: Historically, fewer than 10% of adults with cancer have enrolled in clinical trials. Computational tools have been developed to match patients to trials, but these tools are relevant only when patients need new treatment.
Male Humans Middle Aged Artificial Intelligence Neoplasms Female Disease Progression Aged
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Monitoring multiple sclerosis: digital and fluid phase biomarkers.

Current opinion in neurology Mar 28, 2025
PURPOSE OF REVIEW: Monitoring of disease activity and treatment response in multiple sclerosis (MS) currently relies on the integration of qualitative clinical and radiological data that is of limited predictive value. An array of quantitative digita...
Humans Biomarkers Disease Progression Multiple Sclerosis
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Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.

JACC. Cardiovascular imaging Mar 26, 2025
BACKGROUND: Current treatment paradigms assume aortic regurgitation (AR) patients to be a homogenous population, but varied courses of disease progression and outcomes are observed clinically.
Magnetic Resonance Imaging, Cine Unsupervised Machine Learning Predictive Value of Tests Sex Factors Reproducibility of Results Aortic Valve Insufficiency Risk Factors Humans Aged Machine Learning Adult Disease Progression Male Phenotype Decision Support Techniques Prognosis Time Factors Ventricular Function, Left Severity of Illness Index Retrospective Studies United States Middle Aged Female Aortic Valve Risk Assessment
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Predicting rheumatoid arthritis progression from seronegative undifferentiated arthritis using machine learning: a deep learning model trained on the KURAMA cohort and externally validated with the ANSWER cohort.

Arthritis research & therapy Mar 26, 2025
BACKGROUND: Undifferentiated arthritis (UA) often develops into rheumatoid arthritis (RA), but predicting disease progression from seronegative UA remains challenging because seronegative RA often does not meet the classification criteria. This study...
Aged Adult Male Humans Middle Aged Cohort Studies Disease Progression Machine Learning Arthritis, Rheumatoid Deep Learning Arthritis Female
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Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

PloS one Mar 26, 2025
Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permanent disability and stigma. Described as a disease of poverty, the impact of socioeconomic indicators ...
Disease Progression Malnutrition Nutritional Status Ghana Elephantiasis, Filarial Adult Cross-Sectional Studies Humans Male Middle Aged Machine Learning Female Aged
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Enhancing diagnostic accuracy for HBV-related cirrhosis progression: predictive modeling using combined Golgi protein 73 and α1-microglobulin for the transition from nondecompensated to decompensated cirrhosis.

European journal of gastroenterology & hepatology Mar 21, 2025
BACKGROUND AND AIMS: Chronic hepatitis B poses a major health risk, especially its progression to decompensated cirrhosis. Early prediction is crucial for better outcomes. This study evaluated the predictive power of Golgi protein 73 (GP73), α1-micro...
Disease Progression Case-Control Studies Logistic Models Liver Cirrhosis Machine Learning Humans Aged Hepatitis B, Chronic Biomarkers Adult Membrane Proteins Alanine Transaminase Platelet Count Female Male Age Factors Aspartate Aminotransferases Middle Aged Decision Trees Alpha-Globulins Predictive Value of Tests
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