Enhancing brain metastasis prediction in non-small cell lung cancer: a deep learning-based segmentation and CT radiomics-based ensemble learning model.
Jing GongTing WangZezhou WangXiao ChuTingdan HuMenglei LiWeijun PengFeng FengTong TongYajia GuPublished in: Cancer imaging : the official publication of the International Cancer Imaging Society (2024)
Our results demonstrated that (1) the fusion of radiomics and clinical features can improve the prediction performance in predicting BM risk, (2) the radiomics model generates higher performance than the clinical model, and (3) the radiomics-clinical fusion model has prognostic value in predicting the BMFS and OS of NSCLC patients.
Keyphrases
- deep learning
- lymph node metastasis
- contrast enhanced
- small cell lung cancer
- end stage renal disease
- computed tomography
- chronic kidney disease
- newly diagnosed
- convolutional neural network
- multiple sclerosis
- machine learning
- prognostic factors
- white matter
- positron emission tomography
- subarachnoid hemorrhage
- image quality