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The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning
- Source :
- Scientific Reports, Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020)
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compared with data from 809 survivors who underwent lung cancer surgery. Each of the modeling technique was applied to two feature sets: feature set 1 included clinical and sociodemographic variables, and feature set 2 added HRQOL factors to the variables from feature set 1. One of each developed prediction model was trained with the decision tree (DT), logistic regression (LR), bagging, random forest (RF), and adaptive boosting (AdaBoost) methods, and then, the best algorithm for modeling was determined. The models’ performances were compared using fivefold cross-validation. For feature set 1, there were no significant differences in model accuracies (ranging from 0.647 to 0.713). Among the models in feature set 2, the AdaBoost and RF models outperformed the other prognostic models [area under the curve (AUC) = 0.850, 0.898, 0.981, 0.966, and 0.949 for the DT, LR, bagging, RF and AdaBoost models, respectively] in the test set. Overall, 5-year disease-free lung cancer survival prediction models with MLTs that included HRQOL as well as clinical variables improved predictive performance.
- Subjects :
- Male
Lung Neoplasms
Boosting (machine learning)
Computer science
lcsh:Medicine
Logistic regression
Machine learning
computer.software_genre
Article
Machine Learning
03 medical and health sciences
Medical research
0302 clinical medicine
Cancer Survivors
medicine
Humans
Patient Reported Outcome Measures
030212 general & internal medicine
AdaBoost
lcsh:Science
Signs and symptoms
Lung cancer
Aged
Lung cancer surgery
Multidisciplinary
business.industry
lcsh:R
Health care
Middle Aged
Prognosis
medicine.disease
Random forest
Oncology
Risk factors
Feature (computer vision)
030220 oncology & carcinogenesis
Test set
Quality of Life
lcsh:Q
Female
Artificial intelligence
business
computer
Algorithms
Subjects
Details
- ISSN :
- 20452322
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....92faba315b41c101d80b8b6c3b76a506