AIMC Topic: Disease Progression
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Higher effect sizes for the detection of accelerated brain volume loss and disability progression in multiple sclerosis using deep-learning.
Computers in biology and medicine
Oct 18, 2024
PURPOSE: Clinical validation of "BrainLossNet", a deep learning-based method for fast and robust estimation of brain volume loss (BVL) from longitudinal T1-weighted MRI, for the detection of accelerated BVL in multiple sclerosis (MS) and for the disc...
Identification of key biomarkers for predicting atherosclerosis progression in polycystic ovary syndrome via bioinformatics analysis and machine learning.
Computers in biology and medicine
Oct 12, 2024
OBJECTIVE: Polycystic ovary syndrome (PCOS) is one of the most significant cardiovascular risk factors, playing vital roles in various cardiovascular diseases such as atherosclerosis (AS). This study attempted to explore key biomarkers for predicting...
Predicting Response to Intravesical Bacillus Calmette-Guérin in High-Risk Nonmuscle-Invasive Bladder Cancer Using an Artificial Intelligence-Powered Pathology Assay: Development and Validation in an International 12-Center Cohort.
The Journal of urology
Oct 9, 2024
PURPOSE: There are few markers to identify those likely to recur or progress after treatment with intravesical bacillus Calmette-Guérin (BCG). We developed and validated artificial intelligence (AI)-based histologic assays that extract interpretable ...
Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Oct 1, 2024
Many models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive p...
Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis.
Epilepsy & behavior : E&B
Sep 21, 2024
BACKGROUND AND OBJECTIVES: to identify predictors of progression to refractory status epilepticus (RSE) using a machine learning technique.
Nuclear magnetic resonance-based metabolomics with machine learning for predicting progression from prediabetes to diabetes.
eLife
Sep 20, 2024
BACKGROUND: Identification of individuals with prediabetes who are at high risk of developing diabetes allows for precise interventions. We aimed to determine the role of nuclear magnetic resonance (NMR)-based metabolomic signature in predicting the ...
Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Sep 19, 2024
INTRODUCTION: An increasing number of early-stage lung adenocarcinomas (LUAD) are detected as lung nodules. The radiological features related to LUAD progression warrant further investigation. Exploration is required to bridge the gap between radiomi...
Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.
JACC. Cardiovascular imaging
Sep 18, 2024
BACKGROUND: The development and progression of aortic stenosis (AS) from aortic valve (AV) sclerosis is highly variable and difficult to predict.
Humans
Prognosis
Female
Aortic Valve Stenosis
Reproducibility of Results
Severity of Illness Index
Aortic Valve
Risk Factors
Deep Learning
Predictive Value of Tests
Aged
Diastole
Time Factors
Ventricular Dysfunction, Left
Male
Sclerosis
United States
Echocardiography
Ventricular Function, Left
Calcinosis
Middle Aged
Risk Assessment
Disease Progression
Predicting multiple sclerosis disease progression and outcomes with machine learning and MRI-based biomarkers: a review.
Journal of neurology
Sep 12, 2024
Multiple sclerosis (MS) is a demyelinating neurological disorder with a highly heterogeneous clinical presentation and course of progression. Disease-modifying therapies are the only available treatment, as there is no known cure for the disease. Car...
Machine learning-based model for worsening heart failure risk in Chinese chronic heart failure patients.
ESC heart failure
Sep 7, 2024
AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clini...
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