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postgraduate thesis: A nomogram model for predicting overall survival based on random survival forest and Lasso analysis for stage IV NSCLC patients with brain metastasis from SEER database

TitleA nomogram model for predicting overall survival based on random survival forest and Lasso analysis for stage IV NSCLC patients with brain metastasis from SEER database
Authors
Hu, Mingyang扈铭洋
Issue Date2024
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Hu, M. [扈铭洋]. (2024). A nomogram model for predicting overall survival based on random survival forest and Lasso analysis for stage IV NSCLC patients with brain metastasis from SEER database. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
DegreeMaster of Medical Sciences
SubjectLungs - Cancer
Brain metastasis
Dept/ProgramDiagnostic Radiology
Persistent Identifierhttp://hdl.handle.net/10722/355542

 

DC FieldValueLanguage
dc.contributor.authorHu, Mingyang-
dc.contributor.author扈铭洋-
dc.date.accessioned2025-04-16T08:02:35Z-
dc.date.available2025-04-16T08:02:35Z-
dc.date.issued2024-
dc.identifier.citationHu, M. [扈铭洋]. (2024). A nomogram model for predicting overall survival based on random survival forest and Lasso analysis for stage IV NSCLC patients with brain metastasis from SEER database. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/355542-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshLungs - Cancer-
dc.subject.lcshBrain metastasis-
dc.titleA nomogram model for predicting overall survival based on random survival forest and Lasso analysis for stage IV NSCLC patients with brain metastasis from SEER database-
dc.typePG_Thesis-
dc.description.thesisnameMaster of Medical Sciences-
dc.description.thesislevelMaster-
dc.description.thesisdisciplineDiagnostic Radiology-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2024-
dc.identifier.mmsid991044926591003414-

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