Prediction of Radiation Pneumonitis With Machine Learning in Stage III Lung Cancer: A Pilot Study.
Melek AkcayDurmus EtizMuzaffer MetintasGuntulu AkOzer CelikPublished in: Technology in cancer research & treatment (2021)
When the clinical and dosimetric parameters were evaluated together, the LGBM algorithm had the highest accuracy in predicting RP. However, in order to use this algorithm in clinical practice, it is necessary to increase data diversity and the number of patients by sharing data between centers.
Keyphrases
- machine learning
- big data
- end stage renal disease
- clinical practice
- deep learning
- ejection fraction
- electronic health record
- newly diagnosed
- radiation therapy
- artificial intelligence
- chronic kidney disease
- prognostic factors
- peritoneal dialysis
- patient reported outcomes
- health information
- interstitial lung disease
- idiopathic pulmonary fibrosis