Hybrid Sea Lion Crow Search Algorithm-Based Stacked Autoencoder for Drug Sensitivity Prediction From Cancer Cell Lines

Autor:	Rupali A. Mahajan, Nilofer Karim Shaikh, Atharva Balkrishna Tikhe, Renu Vyas, Smita M. Chavan
Rok vydání:	2022
Předmět:	Computational Theory and Mathematics Artificial Intelligence Computer Science Applications
Zdroj:	International Journal of Swarm Intelligence Research. 13:1-21
ISSN:	1947-9271 1947-9263
Popis:	Providing better therapy to cancer patients remains a major task due to drug resistance of tumor cells. This paper proposes a sea lion crow search algorithm (SLCSA) for drug sensitivity prediction. The drug sensitivity from cultured cell lines is predicted using stacked autoencoder, and the proposed SLCSA is derived from a combination of sea lion optimization (SLnO) and crow search algorithm (CSA). The implemented approach has offered superior results. The maximum value of testing accuracy for normal is 0.920, leukemia is 0.920, NSCLC is 0.912, and urogenital is 0.914.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bef0b17126914a65257a8f53c6b2fa72 https://doi.org/10.4018/ijsir.304723 Zobrazit plný text záznamu