Article

Comprehensive Study of Semi-Supervised Learning for DNA Methylation-based Supervised Classification of Central Nervous System Tumors

2022-02-07

Abstract excerpt

<h4>Background: </h4> Optimal treatment for cancer patients relies on accurate pathological diagnosis. The world health organization has defined almost 100 known central nervous system (CNS) tumors, making the histopathological diagnostic process particularly challenging. To help reduce variability, validation costs, and standardize the histopathological diagnostic process, supervised machine learning techniques u...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e8cc5fe6-22fb-558f-bbbd-3f00e6454109
DOI: 10.21203/rs.3.rs-1284799/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Comprehensive Study of Semi-Supervised Learning for DNA Methylation-based Supervised Classification of Central Nervous System TumorsDOI 10.21203/rs.3.rs-1284799/v1Read

Accurate classification of CNS tumors through DNA methylation data analysis of select genomic regionsSemantic proximity Read

SNUH methylation classifier for CNS tumorsSemantic proximity Read

Improving radiomics-based isocitrate dehydrogenase 1 prediction in glioma patients using semi-supervised machine learning models.Semantic proximity Read

Machine-learning operations streamlined clinical workflows of DNA methylation-based CNS tumor classificationSemantic proximity Read

The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient careSemantic proximity Read

Identification of Methylation Signatures and Rules for Sarcoma Subtypes by Machine Learning MethodsSemantic proximity Read

Diagnostic impact of DNA methylation classification in adult and pediatric CNS tumorsSemantic proximity Read

cIMPACT-NOW update 9: Recommendations on utilization of genome-wide DNA methylation profiling for central nervous system tumor diagnosticsSemantic proximity Read

Comparison of DNA methylation based classification models for precision diagnostics of central nervous system tumorsSemantic proximity Read

CancerSubminer: an integrated framework for cancer subtyping using supervised and unsupervised learning on DNA methylation profilesSemantic proximity Read

Sarcoma classification by DNA methylation profiling in clinical everyday life: the Charité experienceSemantic proximity Read

Unclassifiable CNS tumors in DNA methylation-based classification: clinical challenges and prognostic impactSemantic proximity Read