AIMC Topic: Disease Progression

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Predicting 5-Year EDSS in Multiple Sclerosis with LSTM Networks: A Deep Learning Approach to Disease Progression.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKROUNDS: Multiple Sclerosis (MS) is a neurodegerative disease that is common worldwide, has no definitive cure yet, and negatively affects the individual's quality of life due to disease-related disability. Predicting disability in MS is difficult...

Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis.

Scientific reports
Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes that may occur between visits being missed. Mobile t...

Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer.

World journal of gastroenterology
BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate. Early prognosis of esophageal abnormalities can improve patient survival rates. The progression of esophageal cancer follows a sequence from esophagi...

Early prediction of bone destruction in rheumatoid arthritis through machine learning analysis of plasma metabolites.

Arthritis research & therapy
BACKGROUND: To develop a predictive model for bone destruction in patients with rheumatoid arthritis (RA), based on the characteristics of plasma metabolites and common clinical indicators.

Predictive machine learning and multimodal data to develop highly sensitive, composite biomarkers of disease progression in Friedreich ataxia.

Scientific reports
Friedreich ataxia (FRDA) is a rare, inherited progressive movement disorder for which there is currently no cure. The field urgently requires more sensitive, objective, and clinically relevant biomarkers to enhance the evaluation of treatment efficac...

A self-supervised multimodal deep learning approach to differentiate post-radiotherapy progression from pseudoprogression in glioblastoma.

Scientific reports
Accurate differentiation of pseudoprogression (PsP) from True Progression (TP) following radiotherapy (RT) in glioblastoma patients is crucial for optimal treatment planning. However, this task remains challenging due to the overlapping imaging chara...

Next-Level Prediction of Structural Progression in Knee Osteoarthritis: A Perspective.

International journal of molecular sciences
Osteoarthritis (OA) is a prevalent and disabling chronic disease, with knee OA being the most common form, affecting approximately 73% of individuals over 55 years. Traditional clinical assessments often fail to predict knee structural progression ac...

Accelerated Biological Aging in Exfoliation Glaucoma Assessed by Fundus-Derived Predicted Age and Advanced Glycation End Products.

International journal of molecular sciences
Glaucoma is an age-related neurodegenerative disease characterized by progressive optic nerve damage. Accelerated biological aging, assessed using predicted age derived from fundus images, may serve as a biomarker for glaucoma progression. This study...

Assessment of Elapsed Time Between Dental Radiographs Using Siamese Network.

Studies in health technology and informatics
Recently, machine learning methods have emerged to predict dental disease progression, often relying on costly annotated datasets and frequently exhibiting low generalization performance. This study evaluates the application of Siamese networks for d...

Deep Learning-Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common and progressive respiratory condition characterized by persistent airflow limitation and symptoms such as dyspnea, cough, and sputum production. Acute exacerbations (AE) of COPD (AE...