AIMC Topic: Biomarkers

Clear Filters Showing 1351 to 1360 of 2219 articles

Global gene network exploration based on explainable artificial intelligence approach.

PloS one
In recent years, personalized gene regulatory networks have received significant attention, and interpretation of the multilayer networks has been a critical issue for a comprehensive understanding of gene regulatory systems. Although several statist...

Artificial intelligence identifies inflammation and confirms fibroblast foci as prognostic tissue biomarkers in idiopathic pulmonary fibrosis.

Human pathology
A large number of fibroblast foci (FF) predict mortality in idiopathic pulmonary fibrosis (IPF). Other prognostic histological markers have not been identified. Artificial intelligence (AI) offers a possibility to quantitate possible prognostic histo...

The opportunities and challenges of machine learning in the acute care setting for precision prevention of posttraumatic stress sequelae.

Experimental neurology
Personalized medicine is among the most exciting innovations in recent clinical research, offering the opportunity for tailored screening and management at the individual level. Biomarker-enriched clinical trials have shown increased efficiency and i...

Predictive diagnosis of chronic obstructive pulmonary disease using serum metabolic biomarkers and least-squares support vector machine.

Journal of clinical laboratory analysis
OBJECTIVE: Development of biofluid-based biomarkers is attractive for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking. Thus, here we aimed to identify serum metabolic biomarkers for the diagnosis of COPD.

Calprotectin and Neutrophil Gelatinase-Associated Lipocalin As Biomarkers of Acute Kidney Injury in Acute Coronary Syndrome.

The American journal of the medical sciences
BACKGROUND: Acute kidney injury (AKI) is increasingly being seen in patients with acute coronary syndromes (ACS) and it is associated with higher short-term and long-term morbidity and mortality. Therefore, it is of paramount importance to identify t...

Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers.

Scientific reports
Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to ...

Detecting Vasodilation as Potential Diagnostic Biomarker in Breast Cancer Using Deep Learning-Driven Thermomics.

Biosensors
Breast cancer is the most common cancer in women. Early diagnosis improves outcome and survival, which is the cornerstone of breast cancer treatment. Thermography has been utilized as a complementary diagnostic technique in breast cancer detection. A...

Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study.

BMC pediatrics
BACKGROUND: Stunting affects up to one-third of the children in low-to-middle income countries (LMICs) and has been correlated with decline in cognitive capacity and vaccine immunogenicity. Early identification of infants at risk is critical for earl...