AIMC Topic: Biomarkers

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COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda.

Respiratory medicine
Chronic Obstructive Pulmonary Disease (COPD) is a highly heterogeneous condition projected to become the third leading cause of death worldwide by 2030. To better characterize this condition, clinicians have classified patients sharing certain sympto...

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.

BioMed research international
Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes triggered by microbial activity provide us with the possibility of accurately identifying infection....

Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer's Disease Neuroimaging (ADNI) database.

PloS one
The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on subjects at various stage of symptomatic severity due to Alzheimer's disease. As expected, magnetic r...

Structure equation model and neural network analyses to predict coronary artery lesions in Kawasaki disease: a single-centre retrospective study.

Scientific reports
A new method to predict coronary artery lesions (CALs) in Kawasaki disease (KD) was developed using a mean structure equation model (SEM) and neural networks (Nnet). There were 314 admitted children with KD who met at least four of the six diagnostic...

In vitro and in silico genetic toxicity screening of flavor compounds and other ingredients in tobacco products with emphasis on ENDS.

Journal of applied toxicology : JAT
Electronic nicotine delivery systems (ENDS) are regulated tobacco products and often contain flavor compounds. Given the concern of increased use and the appeal of ENDS by young people, evaluating the potential of flavors to induce DNA damage is impo...

UFO: A tool for unifying biomedical ontology-based semantic similarity calculation, enrichment analysis and visualization.

PloS one
BACKGROUND: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. Important applications of those data include estimating the functional similarity between ontology terms and between annotated biomed...

Converging Multidimensional Sensor and Machine Learning Toward High-Throughput and Biorecognition Element-Free Multidetermination of Extracellular Vesicle Biomarkers.

ACS sensors
Extracellular vesicles (EVs) are a frontier class of circulating biomarkers for the diagnosis and prognosis of different diseases. These lipid structures afford various biomarkers such as the concentrations of the EVs () themselves and carried protei...

AI-based investigation of molecular biomarkers of longevity.

Biogerontology
In this paper, I build deep neural networks of various structures and hyperparameters in order to predict human chronological age based on open-access biochemical indicators and their specifications from the NHANES database. In total, 1152 neural net...

Aptamer based proteomic pilot study reveals a urine signature indicative of pediatric urinary tract infections.

PloS one
OBJECTIVE: Current urinary tract infection (UTI) diagnostic strategies that rely on leukocyte esterase have limited accuracy. We performed an aptamer-based proteomics pilot study to identify urine protein levels that could differentiate a culture pro...

An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.

Cannabis and cannabinoid research
Relatively little is known about the molecular pathways influenced by cannabis use in humans. We used a multi-omics approach to examine protein, metabolomic, and lipid markers in plasma differentiating between cannabis users and nonusers to understa...