A novel hybrid model of flying geese optimization and attention-LSTM for predicting survival outcomes in clear cell renal cell carcinoma

Clear Cell Renal Cell Carcinoma (ccRCC) is the most aggressive and metastatic subtype of renal cell carcinoma and also the type with the highest mortality rate. To enhance survival prediction accuracy and facilitate informed clinical decision-making, this study presents a hybrid model that combines...

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Autors principals:	Cheng-Hong Yang, Tin-Ho Cheung, Yi-Ling Chen, Sin-Hua Moi, Li-Yeh Chuang
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2026-03-01
Col·lecció:	Machine Learning with Applications
Matèries:	Kidney renal clear cell carcinoma Deep learning Feature selected Flying geese optimization algorithm Attention long short-term memory Survival prediction
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S2666827026000113
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