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Yan, Keyue, Fong, Simon, Li, Tengyue, Song, Qun (2024) Multimodal Machine Learning for Prognosis and Survival Prediction in Renal Cell Carcinoma Patients: A Two-Stage Framework with Model Fusion and Interpretability Analysis. Applied Sciences, 14 (13) 5686 doi:10.3390/app14135686

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Reference TypeJournal (article/letter/editorial)
TitleMultimodal Machine Learning for Prognosis and Survival Prediction in Renal Cell Carcinoma Patients: A Two-Stage Framework with Model Fusion and Interpretability Analysis
JournalApplied Sciences
AuthorsYan, KeyueAuthor
Fong, SimonAuthor
Li, TengyueAuthor
Song, QunAuthor
Year2024 (June 29)Volume14
Page(s)5686Issue13
PublisherMDPI AG
DOIdoi:10.3390/app14135686Search in ResearchGate
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Mindat Ref. ID17506891Long-form Identifiermindat:1:5:17506891:5
GUID0
Full ReferenceYan, Keyue, Fong, Simon, Li, Tengyue, Song, Qun (2024) Multimodal Machine Learning for Prognosis and Survival Prediction in Renal Cell Carcinoma Patients: A Two-Stage Framework with Model Fusion and Interpretability Analysis. Applied Sciences, 14 (13) 5686 doi:10.3390/app14135686
Plain TextYan, Keyue, Fong, Simon, Li, Tengyue, Song, Qun (2024) Multimodal Machine Learning for Prognosis and Survival Prediction in Renal Cell Carcinoma Patients: A Two-Stage Framework with Model Fusion and Interpretability Analysis. Applied Sciences, 14 (13) 5686 doi:10.3390/app14135686

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