AIMC Topic: Biomarkers

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Machine learning based prediction of cognitive metrics using major biomarkers in SuperAgers.

Scientific reports
As populations age, understanding cognitive decline and age-related diseases like dementia has become increasingly important. "SuperAgers," individuals over 65 with cognitive abilities similar to those in their 40s, provide a unique perspective on co...

Prediction of coronary heart disease based on klotho levels using machine learning.

Scientific reports
The diagnostic accuracy for coronary heart disease (CHD) needs to be improved. Some studies have indicated that klotho protein levels upon admission comprise an independent risk factor for CHD and have clinical value for predicting CHD. This study ai...

Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.

BMC musculoskeletal disorders
BACKGROUND: Branched-chain amino acids (BCAA) metabolism is significantly associated with osteoarthritis (OA), but the specific mechanism of BCAA related genes (BCAA-RGs) in OA is still unclear. Therefore, this research intended to identify potential...

A novel MRI-based deep learning imaging biomarker for comprehensive assessment of the lenticulostriate artery-neural complex.

BMC medical imaging
OBJECTIVES: To develop a deep learning network for extracting features from the blood-supplying regions of the lenticulostriate artery (LSA) and to establish these features as an imaging biomarker for the comprehensive assessment of the lenticulostri...

Machine learning using scRNA-seq Combined with bulk-seq to identify lactylation-related hub genes in carotid arteriosclerosis.

Scientific reports
Atherosclerosis is a chronic inflammatory disease, this study aims to investigate the immune landscape in carotid atherosclerotic plaque formation and explore diagnostic biomarkers of lactylation-associated genes, so as to gain new insights into unde...

Diagnostic value of small dense low-density lipoprotein and trace elements in coronary artery disease.

Annales de biologie clinique
Coronary artery disease (CAD) is a worldwide leading cause of death. Considering that 20%-40% of patients with CAD have a long asymptomatic period of atherosclerosis, it has become urgent to explore the feasibility of diagnosing CAD at an early stage...

Early prediction of bone destruction in rheumatoid arthritis through machine learning analysis of plasma metabolites.

Arthritis research & therapy
BACKGROUND: To develop a predictive model for bone destruction in patients with rheumatoid arthritis (RA), based on the characteristics of plasma metabolites and common clinical indicators.

Predictive machine learning and multimodal data to develop highly sensitive, composite biomarkers of disease progression in Friedreich ataxia.

Scientific reports
Friedreich ataxia (FRDA) is a rare, inherited progressive movement disorder for which there is currently no cure. The field urgently requires more sensitive, objective, and clinically relevant biomarkers to enhance the evaluation of treatment efficac...

Balancing accuracy and cost in machine learning models for detecting medial vascular calcification in chronic kidney disease: a pilot study.

Scientific reports
Machine learning algorithms that integrate multiple biomarkers are increasingly used in disease detection, yet economic considerations are often overlooked. Medial vascular calcification (mVC), a pathology associated with elevated cardiovascular risk...