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
- contrast enhanced
- lymph node metastasis
- end stage renal disease
- computed tomography
- convolutional neural network
- magnetic resonance imaging
- chronic kidney disease
- ejection fraction
- squamous cell carcinoma
- artificial intelligence
- prognostic factors
- advanced non small cell lung cancer
- dual energy
- breast cancer risk