AI Medical Compendium Topic:
Biomarkers

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Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers.

Scientific reports
Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prevalence worldwide, and can result in serious complications. Therefore, it is of utmost importance to identify individuals at risk as early as possible ...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychiatry research
Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a prot...

Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach.

Cardiovascular diabetology
BACKGROUND: Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as...

Machine Learning-Based Etiologic Subtyping of Ischemic Stroke Using Circulating Exosomal microRNAs.

International journal of molecular sciences
Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (E...

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.

Translational psychiatry
Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention ha...

Analysis of convolutional neural networks for fronto-temporal dementia biomarker discovery.

International journal of computer assisted radiology and surgery
PURPOSE: Frontotemporal lobe dementia (FTD) results from the degeneration of the frontal and temporal lobes. It can manifest in several different ways, leading to the definition of variants characterised by their distinctive symptomatologies. As thes...

Machine learning and artificial intelligence within pediatric autoimmune diseases: applications, challenges, future perspective.

Expert review of clinical immunology
INTRODUCTION: Autoimmune disorders affect 4.5% to 9.4% of children, significantly reducing their quality of life. The diagnosis and prognosis of autoimmune diseases are uncertain because of the variety of onset and development. Machine learning can i...

Lipids balance as a spectroscopy marker of diabetes. Analysis of FTIR spectra by 2D correlation and machine learning analyses.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The number of people suffering from type 2 diabetes has rapidly increased. Taking into account, that elevated intracellular lipid concentrations, as well as their metabolism, are correlated with diminished insulin sensitivity, in this study we would ...

IPF-related new macrophage subpopulations and diagnostic biomarker identification - combine machine learning with single-cell analysis.

Respiratory research
Idiopathic pulmonary fibrosis (IPF) is a chronic disease of unknown etiology that lacks a specific treatment. In IPF, macrophages play a key regulatory role as a major component of the lung immune system, especially during inflammation and fibrosis. ...