An Integrated Data Analysis Using Bioinformatics and Random Forest to Predict Prognosis of Patients With Squamous Cell Lung Cancer
Débora V. C. Lima,
Patrick Terrematte,
Beatriz Stransky
et al.
Abstract:Lung cancer is the leading cause of cancer death worldwide, regardless of gender. Among the types of lung cancer, Lung Squamous Cell Carcinoma (LUSC) is the second most common type, characterized by a diagnosis in advanced stages, a poor prognosis, and a high association with smoking. Due to the severity of lung cancer, it is essential to understand its molecular mechanisms. In this context, this study uses transcriptomic and clinical data to implement bioinformatics pipelines, and machine learning, through ra… Show more
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