AIMC Topic: Cell-Free Nucleic Acids

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Deep centroid: a general deep cascade classifier for biomedical omics data classification.

Bioinformatics (Oxford, England)
MOTIVATION: Classification of samples using biomedical omics data is a widely used method in biomedical research. However, these datasets often possess challenging characteristics, including high dimensionality, limited sample sizes, and inherent bia...

Unlocking Early Cancer Detection: Leveraging Machine Learning in Cell-Free DNA Analysis for Precision Oncology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This study introduces a groundbreaking approach to early cancer detection through the analysis of cell-free DNA (cfDNA), utilizing machine learning algorithms to navigate the complexities of low circulating tumor DNA (ctDNA) fractions and genetic het...

Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Briefings in bioinformatics
Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reduc...

DISMIR: Deep learning-based noninvasive cancer detection by integrating DNA sequence and methylation information of individual cell-free DNA reads.

Briefings in bioinformatics
Detecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel noninvasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise predictions with low-depth cfDN...

miRandola 2017: a curated knowledge base of non-invasive biomarkers.

Nucleic acids research
miRandola (http://mirandola.iit.cnr.it/) is a database of extracellular non-coding RNAs (ncRNAs) that was initially published in 2012, foreseeing the relevance of ncRNAs as non-invasive biomarkers. An increasing amount of experimental evidence shows ...