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An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm
Joint Authors
Huang, Zhangheng
Hu, Chuan
Chi, Changxing
Jiang, Zhe
Tong, Yuexin
Zhao, Chengliang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing.
However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking.
Here, we aimed to establish a model based on artificial intelligence for predicting the 1-year survival rate of NSCLC with BM by using extreme gradient boosting (XGBoost), a large-scale machine learning algorithm.
We selected NSCLC patients with BM between 2010 and 2015 from the Surveillance, Epidemiology, and End Results database.
In total, 5973 cases were enrolled and divided into the training (n=4183) and validation (n=1790) sets.
XGBoost, random forest, support vector machine, and logistic algorithms were used to generate predictive models.
Receiver operating characteristic curves were used to evaluate and compare the predictive performance of each model.
The parameters including tumor size, age, race, sex, primary site, histological subtype, grade, laterality, T stage, N stage, surgery, radiotherapy, chemotherapy, distant metastases to other sites (lung, brain, and liver), and marital status were selected to construct all predictive models.
The XGBoost model had a better performance in both training and validation sets as compared with other models in terms of accuracy.
Our data suggested that the XGBoost model is the most precise and personalized tool for predicting the 1-year survival rate for NSCLC patients with BM.
This model can help the clinicians to design more rational and effective therapeutic strategies.
American Psychological Association (APA)
Huang, Zhangheng& Hu, Chuan& Chi, Changxing& Jiang, Zhe& Tong, Yuexin& Zhao, Chengliang. 2020. An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm. BioMed Research International،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1133179
Modern Language Association (MLA)
Huang, Zhangheng…[et al.]. An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm. BioMed Research International No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1133179
American Medical Association (AMA)
Huang, Zhangheng& Hu, Chuan& Chi, Changxing& Jiang, Zhe& Tong, Yuexin& Zhao, Chengliang. An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1133179
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133179