Handbook of Artificial Intelligence in Biomedical Engineering

Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert’s knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

1. Design of Medical Expert Systems Using Machine Learning TechniquesS. Anto, S. Siamala Devi, K. R. Jothi, and R. Lokeshkumar2. From Design Issues to Validation: Machine Learning in Biomedical EngineeringChrista I L Sharon and V. Suma3. Biomedical Engineering and Informatics Using Artificial IntelligenceK. Padmavathi and A. S. Saranya4. Hybrid Genetic Algorithms for Biomedical ApplicationsSrividya P. and Rajendran Sindhu5. Healthcare Applications of the Biomedical AI SystemS. Shyni Carmel Mary and S. Sasikala6. Applications of Artificial Intelligence in Biomedical EngineeringPuja Sahay Prasad, Vinit Kumar Gunjan, Rashmi Pathak, and Saurabh Mukherjee7. Biomedical Imaging Techniques Using AI SystemsA. Aafreen Nawresh and S. Sasikala8. Analysis of Heart Disease Prediction Using Machine Learning TechniquesN. Hema Priya, N. Gopikarani, and S. Shymala Gowri9. A Review on Patient Monitoring and Diagnosis Assistance by Artificial Intelligence ToolsSindhu Rajendran, Meghamadhuri Vakil, Rhutu Kallur, Vidhya Shree, Praveen Kumar Gupta, and Lingaiya Hiremat10. Semantic Annotation of Healthcare DataM. Manonmani and Sarojini Balakrishanan11. Drug Side Effect Frequency Mining over a Large Twitter Dataset using Apache SparkDennis Hsu, Melody Moh, Teng-Sheng Moh, and Diane Moh12. Deep Learning in Brain SegmentationHao-Yu Yang13.Security and Privacy Issues in Biomedical AI Systems and Potential SolutionsG. Niranjana and Deya Chatterjee14. LiMoS—Live Patient Monitoring SystemT. Ananth Kumar, S. Arunmozhi Selvi, R.S. Rajesh, P. Sivananaintha Perumal, and J. Stalin15. Real-Time Detection of Facial Expressions Using k-NN, SVM, Ensemble classifier and Convolution Neural NetworksA. Sharmila, B. Bhavya, and K. V. N. Kavitha, and P. Mahalakshmi16. Analysis and Interpretation of Uterine Contraction Signals Using Artificial IntelligenceP. Mahalakshmi and S. Suja Priyadharsini17. Enhanced Classification Performance of Cardiotocogram Data for Fetal State Anticipation Using Evolutionary Feature Reduction TechniquesSubha Velappan, Manivanna Boopathi Arumugam, and Zafer Comert18. Deployment of Supervised Machine Learning and Deep Learning Algorithms in Biomedical Text ClassificationG. Kumaravelan and Bichitrananda Behera19. Energy Efficient Optimum Cluster Head Estimation for Body Area NetworksP. Sundareswaran and R.S. Rajesh20. Segmentation and Classification of Tumour Regions from Brain Magnetic Resonance Images by Neural Network-Based TechniqueJ. V. Bibal Benifa and G. Venifa Mini21. A Hypothetical Study in Biomedical Based Artificial Intelligence Systems using Machine Language (ML) RudimentsD. Renuka Devi and S. Sasikala22. Neural Source Connectivity Estimation using particle filter and Granger causality methodsSanthosh Kumar Veeramalla and T. V. K. Hanumantha Rao23. Exploration of Lymph Node-Negative Breast Cancers by Support Vector Machines, Naïve Bayes, and Decision Trees: A Comparative StudyJ. Satya Eswari and Pradeep Singh

Saravanan Krishnan, PhD, is a Senior Assistant Professor in the Department of Computer Science & Engineering at Anna University, Regional Campus, Tirunelveli, Tamilnadu, India. He has 14 years of experience in academics and the IT industry and has published papers in 14 international conferences and 24 international journals. He has also written six book chapters and has edited three books with international publishers. He has done four research projects and two consultancy projects with the total worth of Rs.70 Lakhs. He is an active researcher and academician. Also, he is reviewer for many reputed journals published by Elsevier, Springer, IEEE, etc. He also received an outstanding reviewer certificate from Elsevier, Inc. He is a Mentor of Change for Atal Tinkering Lab of NITI Aayog. He has professional membership with several professional organizations. He has previously worked at Cognizant Technology Solutions, Pvt Ltd. as software associate. He earned his PhD in 2015 and completed his ME (Software Engineering) in 2007. Ramesh Kesavan, PhD, is currently an Assistant Professor in the Department of Computer Applications, Anna University Regional Campus, Tirunelveli, India. His area of research includes cloud computing, big data analytics, data mining, and machine learning. He earned his PhD degree in Computer Science from Anna University, Chennai, India. B. Surendiran, PhD, is an Associate Dean (Academic) and Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Puducherry, Karaikal, India. His research interests include medical imaging, machine learning, dimensionality reduction, and intrusion detection. He has published over 20 papers in international journals and has several conference publications to his credit. He is an active reviewer for various SCI and Scopus journals. He earned his PhD at the National Institute of Technology, Tiruchirappalli, India. G. S. Mahalakshmi, PhD, is currently working as Associate Professor in the Computer Science and Engineering Department at College of Engineering, Anna University, Guindy, Chennai, India. She has vast research experience and has published 180 papers in reputed journals and international conferences. She is also deputy director for the Centre for Entrepreneurship Development, Anna University. She is an active reviewer for various SCI, Scopus journals. Her research interest includes machine learning, artificial intelligence, text mining, and natural language processing.