AI Medical Compendium Topic:
Disease Progression

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Modulation of aldosterone levels by aldosterone synthase promoter polymorphism and association with eGFR decline in patients with chronic kidney disease.

Discovery medicine
To determine whether -344T/C CYP11B2 promoter polymorphism affects serum aldosterone levels and whether this polymorphism is an indicator of eGFR decline in patients with chronic kidney disease. -344 C/T CYP11B2 gene polymorphism analysis was perform...

Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence.

Investigative ophthalmology & visual science
PURPOSE: While millions of individuals show early age-related macular degeneration (AMD) signs, yet have excellent vision, the risk of progression to advanced AMD with legal blindness is highly variable. We suggest means of artificial intelligence to...

Isometry Invariant Shape Descriptors for Abnormality Detection on Brain Surfaces Affected by Alzheimer's Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease (AD), a progressive brain disorder, is the most common neurodegenerative disease in older adults. There is a need for brain structural magnetic resonance imaging (MRI) biomarkers to help assess AD progression and intervention effe...

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Investigative ophthalmology & visual science
PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progres...

A probabilistic pathway score (PROPS) for classification with applications to inflammatory bowel disease.

Bioinformatics (Oxford, England)
SUMMARY: Gene-based supervised machine learning classification models have been widely used to differentiate disease states, predict disease progression and determine effective treatment options. However, many of these classifiers are sensitive to no...

Multi-task fused sparse learning for mild cognitive impairment identification.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Brain functional connectivity network (BFCN) has been widely applied to identify biomarkers for the brain function understanding and brain diseases analysis.