Comparison of machine learning algorithms for the prediction of five-year survival in oral squamous cell carcinoma

Comparison of machine learning algorithms for the prediction of five-year survival in oral squamous cell carcinoma

Background/Aim: Machine learning analyses of cancer outcomes for oral cancer remain sparse compared to other types of cancer like breast or lung. The purpose of the present study was to compare the performance of machine learning algorithms in the prediction of global, recurrence-free five-year surv...

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Bibliographic Details
Main Authors: Alkhadar, H. (Author), Ellis, I. (Author), Gardner, A. (Author), Macluskey, M. (Author), White, S. (Author)
Format: Article
Language:English
Published: Blackwell Publishing Ltd 2021
Subjects:
algorithm
Algorithms
Article
Bayes theorem
Bayes Theorem
bone metastasis
cancer staging
Carcinoma, Squamous Cell
controlled study
decision tree
female
Head and Neck Neoplasms
head and neck tumor
histopathology
human
Humans
lymph vessel
machine learning
Machine Learning
major clinical study
male
Mouth Neoplasms
mouth squamous cell carcinoma
mouth tumor
oral cancer
oral mucosa
perineural invasion
predictive value
priority journal
recurrence free survival
Retrospective Studies
retrospective study
sensitivity and specificity
squamous cell carcinoma
Squamous Cell Carcinoma of Head and Neck
task performance
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