Bio-Inspired Optimization for Medical Data Mining

12Diagnosis of Neurological Disease Using Bioinspired Algorithms

Inam Ul Haq

Faculty of Engineering and Technology, SGT University Gurugram, Haryana, India

Abstract

Neurological diseases have a significant impact on individuals, families, and society. Accurate and timely diagnosis is crucial for effective treatment and management. However, traditional diagnostic methods are often expensive and time- consuming. Recent advancements in bioinspired algorithms offer new possibilities for the diagnosis of neurological diseases. This chapter provides an overview of the role of bioinspired algorithms in neurological disease diagnosis. The chapter begins with an introduction to bioinspired algorithms, covering various types commonly used in healthcare, such as genetic algorithms, neural networks, ant colony optimization, and particle swarm optimization. The applications of bio-inspired algorithms in healthcare are explored, emphasizing their contributions to medical image analysis, disease diagnosis, treatment optimization, and personalized medicine. The chapter then focuses on neurological disease diagnosis, providing an overview of common diseases and current diagnostic techniques. It reviews traditional diagnostic methods and their limitations, highlighting the need for alternative approaches. The application of bioinspired algorithms in neurological disease diagnosis is discussed in detail. Genetic algorithms optimize feature selection and classification algorithms, demonstrated ...