AIMC Topic: Biomarkers

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Glycomics meets artificial intelligence - Potential of glycan analysis for identification of seropositive and seronegative rheumatoid arthritis patients revealed.

Clinica chimica acta; international journal of clinical chemistry
In this study, one hundred serum samples from healthy people and patients with rheumatoid arthritis (RA) were analyzed. Standard immunoassays for detection of 10 different RA markers and analysis of glycan markers on antibodies in 10 different assay ...

Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks.

Artificial intelligence in medicine
Patients with type 2 diabetes mellitus are generally under continuous long-term medical treatment based on anti-diabetic drugs to achieve the desired glucose level. Thus, each patient is associated with a sequence of multiple records for prescription...

High efficiency classification of children with autism spectrum disorder.

PloS one
Autism spectrum disorder (ASD) is a wide-ranging collection of developmental diseases with varying symptoms and degrees of disability. Currently, ASD is diagnosed mainly with psychometric tools, often unable to provide an early and reliable diagnosis...

Mixed Th2 and non-Th2 inflammatory pattern in the asthma-COPD overlap: a network approach.

International journal of chronic obstructive pulmonary disease
INTRODUCTION: The asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is a clinical condition that combines features of those two diseases, and that is difficult to define due to the lack of understanding of the underlying mechanisms. D...

Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

Trends in molecular medicine
There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' ...

Detection of sleep disordered breathing severity using acoustic biomarker and machine learning techniques.

Biomedical engineering online
PURPOSE: Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing ...

Lipid Metabolism in Patients with Anti-N-Methyl-D-Aspartate Receptor Encephalitis.

Neuroimmunomodulation
OBJECTIVE: Lipid metabolism has been implicated in autoimmune disorders, but its relationship with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is unclear. This study examined the association of serum lipids with anti-NMDAR encephalit...

Higher Serum Endocan Level Is Associated with Alzheimer Disease.

Dementia and geriatric cognitive disorders
BACKGROUND: The novel molecule endocan, which is released by endothelium and is regulated by proangiogenic and proinflammatory cytokines, may have a role in the pathophysiology of Alzheimer disease (AD). The aim of this study was to evaluate the rela...

Automatic labeling of molecular biomarkers of immunohistochemistry images using fully convolutional networks.

PloS one
This paper addresses the problem of quantifying biomarkers in multi-stained tissues based on the color and spatial information of microscopy images of the tissue. A deep learning-based method that can automatically localize and quantify the regions e...

Identification of candidate serum biomarkers of childhood-onset growth hormone deficiency using SWATH-MS and feature selection.

Journal of proteomics
UNLABELLED: A typical clinical manifestation of growth hormone deficiency (GHD) is a short stature resulting from delayed growth, but GHD affects bone health, cardiovascular function and metabolic profile and therefore quality of life. Although early...