AIMC Topic: Biomarkers

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A novel method for feature selection based on molecular interactive effect network.

Journal of pharmaceutical and biomedical analysis
Analyzing the biological data by considering the molecule interactions may induce a more accurate identification of disease-related biomarkers. In this study, a novel feature selection method based on molecule (feature) interactive effect network is ...

Heterogeneity in Blood Biomarker Trajectories After Mild TBI Revealed by Unsupervised Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Concussions, also known as mild traumatic brain injury (mTBI), are a growing health challenge. Approximately four million concussions are diagnosed annually in the United States. Concussion is a heterogeneous disorder in causation, symptoms, and outc...

Machine Learning and Pain Outcomes.

Neurosurgery clinics of North America
Machine learning (ML) is an increasingly popular method of data analysis that has meaningful application within the realm of pain management. Current research has used this technique as a tool to refine patient selection for more invasive pain manage...

Metabonomic and transcriptomic analyses of glycosides tablet-induced hepatotoxicity in rats.

Drug and chemical toxicology
We aimed to explore novel biomarkers involved in alterations of metabolism and gene expression related to the hepatotoxic effects of glycosides tablet (TGT) in rats. Rats were randomly divided into groups based on oral administration of TGTs for 6 w...

Molecular Visualization of Early-Stage Acute Kidney Injury with a DNA Framework Nanodevice.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
DNA nanomachines with artificial intelligence have attracted great interest, which may open a new era of precision medicine. However, their in vivo behavior, including early diagnosis and therapeutic effect are limited by their targeting efficiency. ...

Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study.

Cells
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for ...

Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder.

Journal of affective disorders
BACKGROUND: Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).

Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning.

Radiology
Background CT biomarkers both inside and outside the pancreas can potentially be used to diagnose type 2 diabetes mellitus. Previous studies on this topic have shown significant results but were limited by manual methods and small study samples. Purp...