AIMC Topic: Biomarkers

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AI-driven discovery of novel extracellular matrix biomarkers in pelvic organ prolapse.

PLoS computational biology
Deep learning for protein function prediction faces significant challenges in identifying disease-specific proteins. We present Extracellular Matrix Protein Predictor (EPOP), an advanced transfer learning framework leveraging protein language models ...

Machine learning-based identification of small RNA signatures in aqueous humor as a step toward precision diagnosis of glaucoma.

Annals of medicine
BACKGROUND: Glaucoma is a progressive neurodegenerative disease of the optic nerve and one of the leading causes of irreversible blindness worldwide. Small RNAs (including miRNAs) play an important role in the pathogenesis of the disease. Despite ext...

Exploration common biomarkers and pathogenesis of primary Sjögren's syndrome and interstitial lung disease by machine learning and weighted gene co-expression networks.

PloS one
BACKGROUND: Primary Sjögren's syndrome (pSS) is an autoimmune and inflammatory disorder that may affect the lungs, leading to interstitial lung disease (ILD). However, the diagnosis of progression from pSS to ILD is frequently delayed due to unstanda...

Comprehensive identification of immune-related biomarkers and therapeutic targets in preeclampsia: integrative bioinformatics and experimental validation.

BMC pregnancy and childbirth
BACKGROUND: Preeclampsia (PE) is a serious hypertensive complication during pregnancy characterized by immune dysregulation and vascular dysfunction, however, the precise molecular mechanisms and effective therapeutic strategies remain unclear. This ...

Transfer learning-enhanced CNN model for integrative ultrasound and biomarker-based diagnosis of polycystic ovarian disease.

Scientific reports
Polycystic Ovarian Disease (PCOD), also known as Polycystic Ovary Syndrome (PCOS), is a prevalent hormonal and metabolic condition primarily affecting women of reproductive age worldwide. It is typically marked by disrupted ovulation, an increase in ...

Discovering periodontitis biomarkers and therapeutic targets through bioinformatics and ensemble learning analysis.

Scientific reports
Periodontitis, a prevalent inflammatory disease, leads to the progressive destruction of periodontal tissues and poses significant systemic health risks. Despite its widespread impact, the molecular mechanisms driving periodontitis remain poorly unde...

The Identification of Biological Stains at Crime Scenes: A Promising Role for Proteomics and Machine Learning.

Analytical chemistry
Forensic body fluid identification is crucial for reconstructing crime scene events. While DNA analysis provides individualization, it lacks information about the fluid's origin. We developed and evaluated three complementary proteomic approaches usi...

Screening and experimental study of potential biomarkers for ulcerative colitis based on weighted gene co-expression network analysis and machine learning.

Journal of translational medicine
BACKGROUND: Ulcerative colitis (UC) is a chronic nonspecific inflammatory intestinal disease affecting the mucosa and submucosa, characterized by continuous and diffuse active inflammation. However, its underlying pathogenesis remains unclear.

petBrain: a new pipeline for amyloid, Tau tangles and neurodegeneration quantification using PET and MRI.

Alzheimer's research & therapy
INTRODUCTION: Quantification of amyloid plaques (A), neurofibrillary tangles (T), and neurodegeneration (N) using PET and MRI is critical for Alzheimer's disease (AD) diagnosis and prognosis. Existing pipelines face limitations regarding processing t...