ArticleCancer medicine2022
A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.
Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Dynamic Prediction of Clinical Endpoints in Survival Analysis With Machine and Deep Learning: A Systematic Review and Regulatory Perspective.CPT: pharmacometrics & systems pharmacology · 2026Pooled it
- A Systematic Review on Machine Learning Techniques for Survival Analysis in Cancer.Cancer medicine · 2025Pooled it
- Application of machine learning for lung cancer survival prognostication-A systematic review and meta-analysis.Frontiers in artificial intelligence · 2024Pooled it
- Avelumab first-line maintenance in advanced urothelial carcinoma: Complete screening for prognostic and predictive factors using machine learning in the JAVELIN Bladder 100 phase 3 trial.Cancer medicine · 2024Trial
- Integration of Nuclear, Clinical, and Genetic Features for Lung Cancer Subtype Classification and Survival Prediction Based on Machine- and Deep-Learning Models.Diagnostics (Basel, Switzerland) · 2025Article
- Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review.BMC medical research methodology · 2025Article
- A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach.BMC medical informatics and decision making · 2024Article
- Article
- Development and validation of machine learning models to predict survival of patients with resected stage-III NSCLC.Frontiers in oncology · 2023Article
- Prognostic factors of survival in patients with non-small cell lung cancer: a competing risk model using the SEER database.Translational cancer research · 2022Article
- A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.Cancer medicine · 2022Article
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Authors and funding
9 authors.
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Abstract
backgroundAccurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non-small cell lung cancer (NSCLC). The performance of the deep learning network for survival prediction in stage III NSCLC has not been explored.
objectivesThis study aimed to develop a deep learning-based prognostic system that could achieve better predictive performance than the existing staging system for stage III NSCLC.
methodsIn this study, a deep survival learning model (DSLM) for stage III NSCLC was developed based on the Surveillance, Epidemiology, and End Results (SEER) database and was independently tested with another external cohort from our institute. DSLM was compared with the Cox proportional hazard (CPH) and random survival forest (RSF) models. A new prognostic system for stage III NSCLC was also proposed based on the established deep learning model.
resultsThe study included 16,613 patients with stage III NSCLC from the SEER database. DSLM showed the best performance in survival prediction, with a C-index of 0.725 in the validation set, followed by RSF (0.688) and CPH (0.683). DSLM also showed C-indices of 0.719 and 0.665 in the internal and real-world external testing datasets, respectively. In addition, the new prognostic system based on DSLM (AUROC = 0.744) showed better performance than the TNM staging system (AUROC = 0.561).
conclusionIn this study, a new, integrated deep learning-based prognostic model was developed and evaluated for stage III NSCLC. This novel approach may be valuable in improving patient stratification and potentially provide meaningful prognostic information that contributes to personalized therapy.
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