Corrigendum: Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data

Darcie A P Delzell,Brian J Smith,Sara Magnuson,Tabitha Peter,Michelle Smith

doi:10.3389/fonc.2020.00866

Darcie A P Delzell, Brian J Smith + Show 3 more

Open Access

https://doi.org/10.3389/fonc.2020.00866

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Abstract

[This corrects the article DOI: 10.3389/fonc.2019.01393.].

Highlights

The data analyzed for this study were generated by Samantha Dilger, Ph.D and Jessica Sieren, Ph.D (Departments of Radiology and Biomedical Engineering, University of Iowa, Iowa City, IA, United States) who control the rights to the data and do not intend for the data to be shared publicly
This data which was included as Supplementary Material in the original article is being removed
Pathology and radiology reports were reviewed to identify an analysis set of patients who met eligibility criteria of having (a) a solitary lung nodule (5–30 mm) and (b) a malignant nodule confirmed on histopathology or a benign nodule confirmed on histopathology or by size stability for at least 24 months

Summary

Introduction

The data analyzed for this study were generated by Samantha Dilger, Ph.D and Jessica Sieren, Ph.D (Departments of Radiology and Biomedical Engineering, University of Iowa, Iowa City, IA, United States) who control the rights to the data and do not intend for the data to be shared publicly. P. Delzell 1*, Sara Magnuson 1, Tabitha Peter 1, Michelle Smith 1 and Brian J. Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data by Delzell, D.

Results

Conclusion