Development of a VTE Prediction Model Based on Automatically Selected Features in Glioma Patients
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63772-8_34
Reference10 articles.
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4. Xu, Q., Lei, H., Li, X., Li, F., Shi, H., Wang, G., Sun, A., Wang, Y., Peng, B.: Machine learning predicts cancer-associated venous thromboembolism using clinically available variables in gastric cancer patients. Heliyon 9(1) (2023). https://doi.org/10.1016/j.heliyon.2022.e12681
5. He, L., Luo, L., Hou, X., Liao, D., Liu, R., Ouyang, C., Wang, G.: Predicting venous thromboembolism in hospitalized trauma patients: a combination of the Caprini score and data-driven machine learning model. BMC Emergency Med. 21(1) (2021). https://doi.org/10.1186/s12873-021-00447-x
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