CT-based multimodal deep learning for non-invasive overall survival prediction in advanced hepatocellular carcinoma patients treated with immunotherapy.
Yujia XiaJie ZhouXiaolei XunJin ZhangTing WeiRuitian GaoBobby ReddyChao LiuGeoffrey KimZhangsheng YuPublished in: Insights into imaging (2024)
An AI-based prognostic model was developed for advanced HCC using multi-national patients. The model extracts spatial-temporal information from CT scans and integrates it with clinical variables to prognosticate. The model demonstrated superior prognostic ability compared to the conventional size-based RECIST method.
Keyphrases
- computed tomography
- deep learning
- end stage renal disease
- dual energy
- contrast enhanced
- artificial intelligence
- ejection fraction
- image quality
- chronic kidney disease
- magnetic resonance imaging
- machine learning
- peritoneal dialysis
- quality improvement
- magnetic resonance
- pain management
- health information
- convolutional neural network