Bio-Inspired Optimization for Medical Data Mining

Sumit Srivastava, PhD, is the director of Information Technology at Manipal University, Jaipur, India. He obtained his doctorate in data mining from the University of Rajasthan, India. His areas of research involve algorithms, data science, knowledge, and engineering education. He has published more than 70 research papers in review journals.Abhineet Anand, PhD, is a professor in computer science and engineering at Chandigarh University, Mohali, Punjab. He is also the director of the institution. His research includes artificial intelligence, machine learning, cloud computing, optical fiber, etc. He has published in various international journals and conferences, along with four book chapters.Abhishek Kumar, PhD, is an associate professor in the Computer Science & Engineering Department at Chandigarh University, Punjab, India, and is affiliated with the University of Castilla-La Mancha (UCLM), Toledo, Spain. His research areas include artificial intelligence, renewable energy, image processing, and machine learning. In total, he has more than 100 publications in peer-reviewed journals. Kumar is a keynote speaker and a member of various national and international societies in the field of engineering and research. He was awarded the CV Ramen National Award in 2018 in the young researcher and faculty category.Bhavna Saini, PhD, is an assistant professor at Central University, Rajasthan, India. His areas of research include face recognition and fingerprint recognition, data management systems, machine learning, and computer vision. He has numerous books and research papers at national and international levels.Pramod Singh Rathore is an assistant professor in the Department of Computer and Communication Engineering, Manipal University Jaipur, India. He has teaching experience of more than 10 years and has 45 publications in peer-reviewed national and international journals.

• Preface xv1 Bioinspired Algorithms: Opportunities and Challenges 1Shweta Agarwal, Neetu Rani and Amit Vajpayee1.1 Introduction 21.2 Bioinspired Principles and Algorithms 31.3 Opportunities of Bioinspired Algorithms 71.4 Challenges of Bioinspired Algorithms 91.5 Prominent Bioinspired Algorithms 121.6 Applications of Bioinspired Algorithms 181.7 Future Research Directions 211.8 Conclusion 232 Evaluation of Phytochemical Screening and In Vitro Antiurolithiatic Activity of Myristica fragrans by Titrimetry Method Using Machine Learning 31G. Lalitha, S. Surya and M.P. Karthikeyan2.1 Introduction 322.2 Methodology 332.3 Result and Discussion 352.4 Conclusion 383 Parkinson's Disease Detection Using Voice and Speech--Systematic Literature Review 41Ronak Khatwad, Suyash Tiwari, Yash Tripathi, Ajay Nehra and Ashish Sharma3.1 Introduction 423.2 Research Questions 433.3 Method 443.4 Algorithms 603.5 Features 633.6 Conclusion 674 Tumor Detection and Classification 75Hermehar P.S. Bedi, Sukhpreet Kaur and Saumya Rajvanshi4.1 Introduction 764.2 Methods Used for Detection of Tumors 774.3 Methods Used for Classification of Tumours 804.4 Machine Learning 844.5 Deep Learning (DL) 894.6 Performance Metrics 954.7 Method Wise Trend of Using Techniques for Detection of Brain Tumor 974.8 Conclusion 975 Advancements in Tumor Detection and Classification 103Mayank Puri, Aman Garg and Lekha Rani5.1 Introduction 1045.2 Imaging Techniques Used in Tumor Detection and Classification 1055.3 Molecular Biology Techniques 1115.4 Machine Learning and Artificial Intelligence 1155.5 Tumor Classification 1215.6 Challenges and Future Directions 1256 Classification of Brain Tumor Using Machine Learning Techniques: A Comparative Study 129Gandla Shivakanth, Bhaskar Marapelli, A. Shivakumar Reddy, Dasari Manasa and Samtha Konda6.1 Introduction 1306.2 Related Work 1316.3 Datasets 1326.4 Experimental Setup 1336.5 Results and Discussion 1346.6 Conclusion 1367 Exploring the Potential of Dingo Optimizer: A Promising New Metaheuristic Approach 141Anju Yadav and Vivek Kumar Varma7.1 Introduction 1417.2 Architecture of Dingo Optimizer 1427.3 Initialization Process 1447.4 Iteration Phase 1487.6 Other Optimization Techniques 1507.7 Conclusion 1518 Bioinspired Genetic Algorithm in Medical Applications 155Krati Taksali, Arpit Kumar Sharma and Manish Rai8.1 Introduction 1568.2 The Genetic Algorithm 1578.3 Radiology 1588.4 Oncology 1608.5 Endocrinology 1618.6 Obstetrics and Gynecology 1628.7 Pediatrics 1628.8 Surgery 1638.9 Infectious Diseases 1648.10 Radiotherapy 1648.11 Rehabilitation Medicine 1658.12 Neurology 1658.13 Health Care Management 1668.14 Conclusion 1669 Artificial Immune System Algorithms for Optimizing Nanoparticle Design in Targeted Drug Delivery 169Ashish Kumar and Vivek Verma9.1 Introduction 1709.2 Artificial Immune Cells 1719.3 The Artificial Immune System Architecture 17210 Diabetic Retinopathy Detection by Retinal Blood Vessel Segmentation and Classification Using Ensemble Model 185Gandla Shivakanth, K. Aruna Bhaskar, Bechoo Lal, A. Shivakumar Reddy and D. Manasa10.1 Introduction 18610.2 Literature Review 18710.3 Proposed System 18810.4 Conclusion and Future Scope 19811 Diabetes Prognosis Model Using Various Machine Learning Techniques 201Pawan Kumar Patidar, Manish Bhardwaj and Sumit Kumar11.1 Introduction 20211.2 Literature Review 20911.3 Proposed Model 21111.4 Experimental Results and Discussion 21311.5 Conclusion 22212 Diagnosis of Neurological Disease Using Bioinspired Algorithms 227Inam Ul Haq12.1 Introduction 22812.2 Neurological Disease Diagnosis 24412.3 Challenges and Future Directions 26012.4 Conclusion 26413 Optimizing Artificial Neural-Network Using Genetic Algorithm 269Bhavy Pratap and Sulabh Bansal13.1 Introduction 27013.2 Methodology 27813.3 Brief Study on Existing Implementations 28313.4 Comparative Study on Different Implementations 28514 Bioinspired Applications in the Medical Industry: A Case Study 289Alankrita Aggarwal and Mohit Lalit14.1 Introduction 29014.2 Overview of Bioinspired Algorithms 29114.3 Applications of Bioinspired Algorithms in Medical Field 29614.4 Review of the Case Studies 29714.5 Case Study 29714.6 Some Examples of the Case Studies Related to Medical Field and Can Be Solved with Bioinspired Algorithms 30014.7 Future Directions and Recommendations for Future Research 30214.8 Conclusion and Summary of Findings 306References 307Index 309