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Predicting Lymphoma Development by Exploiting Genetic Variants and Clinical Findings in a Machine Learning-Based Methodology With Ensemble Classifiers in a Cohort of Sjögren's Syndrome Patients
Lymphoma development constitutes one of the most serious clinico-pathological manifestations of patients with Sjögren's Syndrome (SS). Over the last decades the risk for lymphomagenesis in SS patients has been studied aiming to identify novel biomarkers and risk factors predicting lymphoma deve...
| Formato: | Online Artículo Texto |
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| Lenguaje: | English |
| Publicado: |
IEEE
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979630/ https://www.ncbi.nlm.nih.gov/pubmed/35402956 http://dx.doi.org/10.1109/OJEMB.2020.2965191 |