Multi-disease big data analysis using beetle swarm optimization and an adaptive neuro-fuzzy inference system

Abstract Healthcare organizations and Health Monitoring Systems generate large volumes of complex data, which offer the opportunity for innovative investigations in medical decision making. In this paper, we propose a beetle swarm optimization adaptive neuro-fuzzy inference system (BSO-ANFIS) model heart disease multi-disease diagnosis. The main components our analytics pipeline are modified crow search algorithm, used feature extraction, an ANFIS classification whose parameters optimized by means BSO algorithm. accuracy achieved detection is $$99.1\%$$ 99.1 % with $$99.37\%$$ 99.37 precision. classification, $$96.08\%$$ 96.08 $$98.63\%$$ 98.63 results from both tasks prove comparative advantage proposed BSO-ANFIS algorithm over competitor models.