REFERENCES
- Saadaldeen Rashid Ahmed Ahmed1, Israa Al_Barazanchi2, Ammar Mhana3 ,
Haider Rasheed and Abdulshaheed” Lung cancer classification using
data mining and supervised learning algorithms on multi-dimensional
data set” Periodicals of Engineering and Natural Sciences ISSN
2303-4521 Vol. 7, No. 2, June 2019, pp.438-447 2019.
- Jafar, ALzubi, Balasubramaniyan Bharathikannan, Sudeep Tanwar,
Ramachandran Manikandan, Ashish Khanna, Chandrasekar Thaventhiran,
“Boosted neural network ensemble classification for lung cancer
disease diagnosis”, https://doi.org/10.1016/j.asoc.2019.04.031
, 1568-4946/© 2019.
- JAYADEEP PAT, “Gene Expression Analysis for Early Lung Cancer
Prediction Using Machine Learning Techniques: An Eco-Genomics
Approach”,
http://www.ieee.org/publications_standards/publications/rights/index.html
, IEEE 2169-3536 2018.
- James A. Bartholomai and Hermann B. Frieboes, “Lung Cancer Survival
Prediction via Machine Learning Regression, Classification, and
Statistical Techniques”, IEEE 978-1-5386-7568-7/18/$31.00 ©2018.
- Mohamad Rabbani, Jonathan Kanevsky, Kamran Kafi, Florent Chandelier
and Francis J. Giles, “Role of artificial intelligence in the care of
patients with nonsmall cell lung cancer”,
https://doi.org/10.1111/eci.12901 , © 2018.
- Gur Amrit Pal Singh and P. K. Gupta, “Performance analysis of various
machine learning-based approaches for detection and classification of
lung cancer in humans”,
https://doi.org/10.1007/s00521-018-3518-x , The Natural
Computing Applications Forum 27 April 2018.
- Muhammad Imran Faisal, Saba Bashir, Zain Sikandar Khan, Farhan Hassan
Khan,” An Evaluation of Machine Learning Classifiers and Ensembles
for Early Stage Prediction of Lung Cancer” 2020.
- Darcie A. P. Delzell, Sara Magnuson, Tabitha Peter, Michelle Smith and
Brian J. Smith, “Machine Learning and Feature Selection Methods for
Disease Classification With Application to Lung Cancer Screening Image
Data”, https://doi.org/10.3389/fonc.2019.01393 ,
December 2019.
- Lakshmanaprabu S.K, Sachi Nandan mohanty, Shankar K , Arunkumar N and
Gustavo Ramirez, ” Optimal Deep Learning Model for Classification of
Lung Cancer on CT Images”,
https://doi.org/10.1016/j.future.2018.10.009 , 4 October 2018.
- Jay Kumar Raghavan Nair, Umar Abid Saeed, Connor C. McDougall, Ali
Sabri, Mmed, Bojan Kovacina, B. V. S. Raidu, Riaz Ahmed Khokhar,
Stephan, Vera Hirsh, Chankowsky Jeffrey, Leon C. Van Kempen, and Jana
Taylor, “Radiogenomic Models Using Machine Learning Techniques to
Predict EGFR Mutations in Non-Small Cell Lung Cancer”,
https://doi.org/10.1177/0846537119899526 , The Author(s) 2020.
- Diego Ardila , Atilla P. Kiraly, Sujeeth Bharadwaj, Bokyung Choi,
Joshua J. Reicher , Lily Peng, Daniel Tse , Mozziyar Etemadi, Wenxing
Ye, Greg Corrado, David P. Naidich and Shravya Shetty, “End-to-end
lung cancer screening with three-dimensional deep learning on low-dose
chest computed tomography”,
https://doi.org/10.1038/s41591-019-0447-x ,
http://www.nature.com/naturemedicine JUNE 2019.
- Ibrahim M. Nasser and Samy S. Abu-Naser, “Lung Cancer Detection Using
Artificial Neural Network”, International Journal of Engineering and
Information Systems (IJEAIS),
https://ssrn.com/abstract=3369062 , March – 2019.
- Yiwen Xu, Ahmed Hosny, Roman Zeleznik, Chintan Parmar, Thibaud
Coroller, Idalid Franco, Raymond H. Mak, and Hugo J.W.L. Aerts, “Deep
Learning Predicts Lung Cancer Treatment Response from Serial Medical
Imaging”, 10.1158/1078-0432.CCR-18-2495 , American Association for
Cancer Research, http://clincancerres.aacrjournals.org/ ,
April 23 2019.
- Nasrullah Nasrullah, Jun Sang, Mohammad S. Alam, Muhammad Mateen, Bin
Cai and Haibo Hu, “Automated Lung Nodule Detection and Classification
Using Deep Learning Combined with Multiple Strategies”,http://www.mdpi.com/journal/sensors , 26 August 2019.
- Kun-Hsing Yu, Tsung-Lu Michael Lee, Ming-Hsuan Yen, S C Kou, Bruce
Rosen, Jung-Hsien Chiang and Isaac S Kohane, “Reproducible Machine
Learning Methods for Lung Cancer Detection Using Computed Tomography
Images: Algorithm Development and Validation”,http://dx.doi.org/10.2196/16709 , JOURNAL OF MEDICAL
INTERNET RESEARCH, J Med Internet Res 2020.
- Ning Langa, Yang Zhangb, Enlong Zhanga, Jiahui Zhanga, Daniel Chowb,
Peter Changb, Hon J. Yub, Huishu Yuana and Min-Ying Su,
“Differentiation of spinal metastases originated from lung and other
cancers using radiomics and deep learning based on DCE-MRI”,
https://www.elsevier.com/locate/mri ,https://doi.org/10.1016/j.mri.2019.02.013 , d 28 February2019.
- Janee Alam, Sabrina Alam and Alamgir Hossan, “Multi-Stage Lung Cancer
Detection and Prediction Using Multi-class SVM Classifier”, 2019.
- Hann-Hsiang Chaol, Gilmer Valdes, Jose M. Luna, Marina Heskel, Abigail
T. Berman, Timothy D. Solberg and Charles B. Simone, ” Exploratory
analysis using machine learning to predict for chest wall pain in
patients with stage I non‐small‐cell lung cancer treated with
stereotactic body radiation therapy”,http://www.wileyonlinelibrary.com/journal/JACMP ,
Accepted: 13 June 2018.
- Ahmed Hosny, Chintan Parmar, Thibaud P. Coroller, Patrick Grossmann,
Roman Zeleznik, Avnish Kumar, Johan Bussink, Robert J. Gillies,
Raymond H. Mak and Hugo J. W. L. Aerts, “Deep learning for lung
cancer prognostication: A retrospective multi-cohort radiomics
study”, PLOS Medicinehttps://doi.org/10.1371/journal.pmed.1002711, November
30, 2018.
- Ruchita Tekade and Pro. Dr. k. Rajeswari, “Lung Cancer detection and
Classification using Deep learning ”, 2018 Fourth International
Conference on computing communication and Automation, IEEE 2018.