AIMC Topic: Biomarkers

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Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders.

Statistics in medicine
Feature selection is an important initial step of exploratory analysis in biomedical studies. Its main objective is to eliminate the covariates that are uncorrelated with the outcome. For highly correlated covariates, traditional feature selection me...

Assessment of lipid peroxidation and artificial neural network models in early Alzheimer Disease diagnosis.

Clinical biochemistry
OBJECTIVE: Lipid peroxidation constitutes a molecular mechanism involved in early Alzheimer Disease (AD) stages, and artificial neural network (ANN) analysis is a promising non-linear regression model, characterized by its high flexibility and utilit...

The Model of Aging Acceleration Network Reveals the Correlation of Alzheimer's Disease and Aging at System Level.

BioMed research international
As the incidence of senile dementia continues to increase, researches on Alzheimer's disease (AD) have become more and more important. Several studies have reported that there is a close relationship between AD and aging. Some researchers even pointe...

Disability in multiple sclerosis is associated with age and inflammatory, metabolic and oxidative/nitrosative stress biomarkers: results of multivariate and machine learning procedures.

Metabolic brain disease
The aim of this study was to evaluate the immune-inflammatory, metabolic, and nitro-oxidative stress (IM&NO) biomarkers as predictors of disability in multiple sclerosis (MS) patients. A total of 122 patients with MS were included; their disability w...

ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction.

BMC medical genomics
BACKGROUND: Feature selection or scoring methods for the detection of biomarkers are essential in bioinformatics. Various feature selection methods have been developed for the detection of biomarkers, and several studies have employed information-the...

Application of artificial neural network model in diagnosis of Alzheimer's disease.

BMC neurology
BACKGROUND: Alzheimer's disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish an early warning model using artificial neural network (ANN) for early diagnosis of AD and to explo...

Discovery of food identity markers by metabolomics and machine learning technology.

Scientific reports
Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to...

Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity.

Trends in pharmacological sciences
First published in 2016, predictors of chronological and biological age developed using deep learning (DL) are rapidly gaining popularity in the aging research community. These deep aging clocks can be used in a broad range of applications in the pha...

[Maturity Onset Diabetes of the Young: case report].

Revista medica del Instituto Mexicano del Seguro Social
BACKGROUND: Maturity Onset Diabetes of the Young (MODY) is a type of diabetes that results from mutations in 13 known genes that play a role in the development and maturation of pancreatic beta cells. It represents 5% of all individuals diagnosed wit...

GAIL: An interactive webserver for inference and dynamic visualization of gene-gene associations based on gene ontology guided mining of biomedical literature.

PloS one
In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative b...