ArticleScientific reports2023
Development of artificial intelligence prognostic model for surgically resected non-small cell lung cancer.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed.
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- Development and internal validation of an XGBoost-based prognostic prediction model and risk stratification system for overall survival in pediatric neuroblastoma: a SEER-based study.Translational pediatrics · 2026Article
- Multimodal multitask deep learning for grading management system in non-small cell lung cancer.Nature communications · 2026Article
- SXRNSCLC-PRSP software to predict prognostic risk and survival in patients with resected TJournal of cardiothoracic surgery · 2026Article
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- LANTERN-XGB: An Interpretable Multi-Modal Machine Learning for Improving Clinical Decision-Making in Lung Cancer.International journal of molecular sciences · 2026Article
- Integrative transcriptomics and machine learning reveal key regulatory genes for meat quality traits in pigs.BMC genomics · 2026Article
- Artificial intelligence and machine learning in non-small cell lung cancer: the current state of the science on multi-omic applications.BMC medical research methodology · 2026Review
- Quantum-enhanced multimodal prognostic transformer for skin disease progression prediction and visualization.Scientific reports · 2026Article
- A Systematic Literature Review on Integrated Deep Learning and Multiagent Vision-Language Frameworks for Pathology Image Analysis and Report Generation.Computational and structural biotechnology journal · 2026Review
- Development of a machine learning-based model to predict prognosis of resected invasive pulmonary adenocarcinoma.Journal of thoracic disease · 2025Article
- Artificial intelligence-assisted machine learning models for predicting lung cancer survival.Asia-Pacific journal of oncology nursing · 2025Article
- Review
- Interpretable machine learning models for survival prediction in prostate cancer bone metastases.Scientific reports · 2025Article
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Risk prediction model for pneumothorax or pleural effusion after microwave ablation in patients with lung malignancy.Heliyon · 2024Article
- Application of three-dimensional printed models with near-infrared fluorescence technology in video-assisted thoracoscopic surgery segmentectomy: a single-center propensity-score matching analysis.Journal of thoracic disease · 2024Article
- Development of a machine learning-based model to predict prognosis of alpha-fetoprotein-positive hepatocellular carcinoma.Journal of translational medicine · 2024Article
- Navigating the Future: A Comprehensive Review of Artificial Intelligence Applications in Gastrointestinal Cancer.Cureus · 2024Review
- Machine learning-based prediction of 5-year survival in elderly NSCLC patients using oxidative stress markers.Frontiers in oncology · 2024Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There are great expectations for artificial intelligence (AI) in medicine. We aimed to develop an AI prognostic model for surgically resected non-small cell lung cancer (NSCLC). This study enrolled 1049 patients with pathological stage I-IIIA surgically resected NSCLC at Kyushu University. We set 17 clinicopathological factors and 30 preoperative and 22 postoperative blood test results as explanatory variables. Disease-free survival (DFS), overall survival (OS), and cancer-specific survival (CSS) were set as objective variables. The eXtreme Gradient Boosting (XGBoost) was used as the machine learning algorithm. The median age was 69 (23-89) years, and 605 patients (57.7%) were male. The numbers of patients with pathological stage IA, IB, IIA, IIB, and IIIA were 553 (52.7%), 223 (21.4%), 100 (9.5%), 55 (5.3%), and 118 (11.2%), respectively. The 5-year DFS, OS, and CSS rates were 71.0%, 82.8%, and 88.7%, respectively. Our AI prognostic model showed that the areas under the curve of the receiver operating characteristic curves of DFS, OS, and CSS at 5 years were 0.890, 0.926, and 0.960, respectively. The AI prognostic model using XGBoost showed good prediction accuracy and provided accurate predictive probability of postoperative prognosis of NSCLC.
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