High Performance Computing for Intelligent Medical Systems
Description
Modern medicine and healthcare are highly dependent on engineering, employing instrumentation and computer systems to aid investigation, diagnosis, treatment and patient management. Large amounts of data are generated in every stage, especially with the advent of wearable and smart medical devices.
The significant developments in the field of computational intelligence, combined with the emergence of high-performance computing is impacting society in many ways, and the health sector is no exception. High-performance computing is a powerful option for working with large amounts of data, where it can perform complex tasks with both high speed and accuracy. The interface of high-performance computing, computational intelligence and medical science has seen the emergence of intelligent medical systems, used to manage the generation, storage and processing of large amounts of medical data. Deep computational architectures, with capabilities such as low-level feature extraction and data augmentation, can provide new directions to medical research, providing a deeper insight into many healthcare and medical problems. It can also aid in controlling, analyzing and the management of medical applications and can provide significant improvement in the quality of life and efficacy of clinical treatment. However, the successful application of high-performance computing in medicine requires in-depth knowledge and understanding of medical systems.
This book focuses on the advances and applications of high-performance computing for medical systems and provides an insight into the latest developments in the field. It will help readers to understand the high-performance computing research domain as related to intelligent medical systems, its effect on our lives and its present limitations.
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Persons
Irshad Ahmad Ansari has been working at the Department of Electronics and Communication Engineering, at PDPM Indian Institute of Information Technology, Design, and Manufacturing (IIITDM) Jabalpur, India since 2017. He received BTech degree in Electronics and Communication Engineering from Gautam Buddha Technical University, Lucknow, India in 2010, MTech Degree in Control and Instrumentation from Dr B R Ambedkar National Institute of Technology Jalandhar, Punjab, India in 2012. He completed his PhD from IIT Roorkee with MHRD teaching assistantship and subsequently joined Gwangju Institute of Science and Technology, South Korea as a Postdoctoral fellow. His major research interests include image processing, signal processing, soft computing, brain-computer interface and machine learning. He is a Senior IEEE member. He has authored more than 32 research papers in various international journals and conferences.
Varun Bajaj (PhD, MIEEE 16 SMIEEE20) has been in the department of Electronics and Communication Engineering, at the Indian Institute of Information Technology, Design, and Manufacturing (IIITDM) Jabalpur, India since 2014. He worked as a visiting faculty in IIITDM Jabalpur from September 2013 to March 2014. He worked as Assistant Professor at the Department of Electronics and Instrumentation, Shri Vaishnav Institute of Technology and Science, Indore, India during 2009-2010. He received BE degree in Electronics and Communication Engineering from Rajiv Gandhi Technological University, Bhopal, India in 2006, MTech Degree with Honors in Microelectronics and VLSI design from Shri Govindram Seksaria Institute of Technology & Science, Indore, India in 2009. He received his PhD degree in the Discipline of Electrical Engineering, at the Indian Institute of Technology Indore, India in 2014. He is an Associate Editor of IEEE Sensor Journal and Subject Editor-in-Chief of IET Electronics Letters. He served as a Subject Editor of IET Electronics Letters from Nov. 2018 to June 2020. He is Senior Member IEEE June 2020, MIEEE 16-20, and also contributes as an active technical reviewer of leading International journals of IEEE, IET, and Elsevier, etc. He has authored more than 110 research papers in various reputed international journals/conferences like IEEE Transactions, Elsevier, Springer, IOP etc. He has edited IOP books, and CRC Press (Taylor & Francis Group). The citation impact of his publications is around 2365 citations, h index of 24, and i10 index of 55 (Google Scholar Sep 2020). He is a recipient of various reputed national and international awards. His research interests include biomedical signal processing, image processing, time-frequency analysis, and computer-aided medical diagnosis.
Content
Preface 1 Automatic Detection of Hypertension by Flexible Analytic Wavelet Transform using Electrocardiogram Signals 2 Computational Intelligence in Surface Electromyogram Signal Classification 3 Analysis of IoT interventions to solve voice Pathologies Challenges 4 Deep learning for Cuffless Blood Pressure Monitoring 5 Reliability of machine learning methods for diagnosis and prognosis during COVID-19 pandemic: A comprehensive critical review 6 Forecasting Confirmed Cases of Corona Patients in India using Regression and Gaussian Analysis 7 A model for advanced patient feedback procedures in diagnostics 8 Soft Computing Techniques for Efficient Processing of Large Medical Data 9 A Comparison of Parkinson Disease Prediction Using Ensemble Data Mining Techniques with Features Selection Methods 10 A Comparative Analysis of Image Enhancement Techniques for Detection of Microcalcification in Screening Mammogram 11 Computational Intelligence for Eye Disease Detection 12 Recent trends in Medical Image Segmentation with Special Focus on Brain Tumours and Retinal Images. 13 Analysis of AI-based PID Controller for Health Care System
