Machine learning with the cancer genome atlas head and neck squamous cell carcinoma dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality

Machine learning with the cancer genome atlas head and neck squamous cell carcinoma dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality

In recent years, more data is becoming available for historical oncology case analysis. A large dataset that describes over 500 patient cases of Head and Neck Squamous Cell Carcinoma is a potential goldmine for finding ways to improve oncological decision support. Unfortunately, the best approaches...

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Bibliographic Details
Main Author: Rendleman, Michael
Other Authors: Casavant, Thomas L.
Format: Others
Language:English
Published: University of Iowa 2019
Subjects:
cancer
dimensionality reduction
head and neck cancer
imputation
machine learning
mutation significance
Electrical and Computer Engineering
Online Access:https://ir.uiowa.edu/etd/6841
https://ir.uiowa.edu/cgi/viewcontent.cgi?article=8375&context=etd

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