Machine Learning Models to Predict Primary Sites of Metastatic Cervical Carcinoma From Unknown Primary

Machine Learning Models to Predict Primary Sites of Metastatic Cervical Carcinoma From Unknown Primary

Metastatic cervical carcinoma from unknown primary (MCCUP) accounts for 1–4% of all head and neck tumors, and identifying the primary site in MCCUP is challenging. The most common histopathological type of MCCUP is squamous cell carcinoma (SCC), and it remains difficult to identify the primary site...

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Bibliographic Details
Main Authors: Di Lu, Jianjun Jiang, Xiguang Liu, He Wang, Siyang Feng, Xiaoshun Shi, Zhizhi Wang, Zhiming Chen, Xuebin Yan, Hua Wu, Kaican Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-12-01
Series:Frontiers in Genetics
Subjects:
metastatic cervical carcinoma from unknown primary
random forest
neural network
support vector machine
predict
primary sites
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.614823/full

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