Liver Cancer Algorithm: A novel bio-inspired optimizer

• Published in: Computers in biology and medicine Vol. 165; p. 107389
• Main Authors: Houssein, Essam H., Oliva, Diego, Samee, Nagwan Abdel, Mahmoud, Noha F., Emam, Marwa M.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2023; Elsevier Limited
• Subjects: Algorithms; Amine oxidase (flavin-containing); Benchmarks; Bio-inspired; Biomedical data; Coronaviruses; Datasets; Evolutionary algorithms; Evolutionary computation; Feature selection; Feature selection (FS); Genetic algorithms; Herd immunity; Heuristic methods; Internal Medicine; Liver cancer; Liver Cancer Algorithm (LCA); Metaheuristic algorithms (MAs); Operators (mathematics); Optimization; Optimization algorithms; Other; Particle swarm optimization; Random opposition-based learning (ROBL); Runge-Kutta method; Support vector machines; Tumors; Liver Cancer Algorithm (LCA); Bio-inspired; Random opposition-based learning (ROBL); Feature selection (FS); Metaheuristic algorithms (MAs); Optimization

This paper introduces a new bio-inspired optimization algorithm named the Liver Cancer Algorithm (LCA), which mimics the liver tumor growth and takeover process. It uses an evolutionary search approach that simulates the behavior of liver tumors when taking over the liver organ. The tumor’s ability...