ArticleBioMed research international2022
A Machine Learning Approach Using XGBoost Predicts Lung Metastasis in Patients with Ovarian Cancer.
Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Developing a prediction model to predict the incidence of metastasis in lung cancer patients using artificial intelligence techniques.BMC pulmonary medicine · 2026Article
- Article
- The role of ITGA3 expression in predicting liver metastasis in patients with epithelial ovarian cancer.BMC medical genomics · 2025Article
- Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy.Scientific reports · 2025Article
- Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.Cancer immunology, immunotherapy : CII · 2025Article
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8 authors.
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Abstract
Background: Liver metastasis (LM) is an independent risk factor that affects the prognosis of patients with ovarian cancer; however, there is still a lack of prediction. This study developed a limit gradient enhancement (XGBoost) to predict the risk of lung metastasis in newly diagnosed patients with ovarian cancer, thereby improving prediction efficiency. Results: The results of the XGBoost algorithm showed that the top five important factors were age, laterality, histological type, grade, and marital status. XGBoost showed good discriminative ability, with an AUC of 0.843. Accuracy, sensitivity, and specificity were 0.982, 1.000, and 0.686, respectively. Conclusion: This study is the first to develop a machine-learning-based prediction model for lung metastasis in patients with ovarian cancer. The prediction model based on the XGBoost algorithm has a higher accuracy rate than traditional logistic regression and can be used to predict the risk of lung metastasis in newly diagnosed patients with ovarian cancer.
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