Addresses the design challenges and research in electronic device applications in healthcare and biomedical systems, exploring the blending of mobile communications, network technologies, medical sensors, etc. for health diagnosis and monitoring. It looks at machine learning, CNNs, smartphone-based devices, IoT, and other smart technologies.
Addresses the design challenges and research in electronic device applications in healthcare and biomedical systems, exploring the blending of mobile communications, network technologies, medical sensors, etc. for health diagnosis and monitoring. It looks at machine learning, CNNs, smartphone-based devices, IoT, and other smart technologies.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Rajesh K. Kesharwani, PhD, MTech, is Associate Professor in the Department of Computer Application at Nehru Gram Bharati (Deemed to be University), Prayagraj, India. He has more than 12 years of research experience and nine years of teaching experience at various institutes of India, imparting bioinformatics and biotechnology education. He has received several awards, including the NASI-Swarna Jayanti Puruskar by the National Academy of Sciences of India. He has supervised one PhD and more than 20 undergraduate and graduate students for their research work. Dr. Kesharwani has authored over 55 peer-reviewed articles, 35 book chapters, and 27 edited books with international publishers. He has been a member of many scientific communities as well as a reviewer for many international journals. He has presented many papers at various national and international conferences. Dr. Kesharwani received his PhD from the Indian Institute of Information Technology, Allahabad, and worked at NIT Warangal for two semesters. He was a recipient of a Ministry of Human Resource Development (India) Fellowship and a Senior Research Fellowship from the Indian Council of Medical Research, India. His research fields of interest are medical informatics, protein structure and function prediction, computer-aided drug designing, structural biology, drug delivery, cancer biology, nanobiotechnology, and biomedical sciences. Upendra Kumar, PhD, is Assistant Professor in the Department of Computer Science and Engineering at the Institute of Engineering and Technology, Dr. A. P. J. Abdul Kalam Technical University, Uttar Pradesh, Lucknow, India.He has around four years of industrial experience at Tata Consultancy Services, where he worked on many corporate projects as a JAVA/J2EE developer. He has more than 10 years of teaching and research experience. His area of research interest is digital image processing, machine learning, medical informatics, biomedical signal processing, fractal and chaos analysis, embedded systems and robotics with embedded C, medical imaging and diagnostic system, big data analytics, etc. He has published many papers in international and national journals and conferences and has published several book chapters. He has published many books and book chapters with international publishers and filed one Indian patent with the collaboration of IIIT Allahabad. Currently he is supervising four research scholars who are on the final stage of their PhD thesis work. He has delivered expert lectures at various international and national conferences, workshops, and seminars. He is a member of several review committees of national and international journals, conferences, and professional bodies. Apart from teaching and research work, he has held an administrative role working as Deputy Dean of Students Welfare at the Institute of Engineering and Technology. Dr. Kumar has an MTech in IT from IIIT Allahabad and a PhD in Computer Science & Engineering from Dr. A.P.J. Abdul Kalam Technical University, UP, Lucknow, India. Raj K. Keservani, PhD, MPharm, is Associate Professor, Faculty of B. Pharmacy, CSM Group of Institutions, Prayagraj, India. He has more than 12 years of academic (teaching) experience at various institutes of India in pharmaceutical education. He has supervised more than 25 undergraduate students for their research work. He has published over 30 peer-reviewed papers in the field of pharmaceutical sciences in national and international journals, 50 book chapters, three co-authored books, and 27 edited books. He also holds one patent. He is also active as a reviewer for several international scientific journals. Dr. Keservani is a life member of the Society of Pharmaceutical Education and Research. His research interests include nutraceutical and functional foods, novel drug delivery systems, transdermal drug delivery/drug delivery, health science, cancer biology, and neurobiology. Dr. Keservani graduated with a pharmacy degree from the Department of Pharmacy, Kumaun University, Nainital, Uttarakhand, India. He received his MPharm) (specialization in pharmaceutics) from the School of Pharmaceutical Sciences, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India. He received his PhD degree from IKG Punjab Technical University, Jalandhar, Punjab, India.
Inhaltsangabe
1. Machine Learning in the Healthcare Domain 2. Emerging Trends in IoT with Machine Learning Techniques for Biomedical and Healthcare Systems 3. Machine Learning Techniques Used for Diagnosing Cardiac Abnormalities Using Electrocardiograms 4. Predicting Resilience of Blood Groups Against the COVID-19 Delta Variant Using Machine Learning 5. A Key Role of Convolutional Neural Networks in Biomedical Imaging Applications 6. The Most Recent Developments and Applications of Smartphone-Based Devices in Biomedical and mHealth 7. Real-Time Health Monitoring Using IoT Sensors 8. IC Design: An Approach of Study in Biomedical and mHealth Care Applications 9. Experimental Setup and Analysis of Energy Harvesting Systems for a Low Power Biomedical Application: Lab on Chip Application of Impedance Micropump and Microfluidic Logic Gate 10. Analysis and Application of Power Amplifiers to Biomedical Instrumentation
1. Machine Learning in the Healthcare Domain 2. Emerging Trends in IoT with Machine Learning Techniques for Biomedical and Healthcare Systems 3. Machine Learning Techniques Used for Diagnosing Cardiac Abnormalities Using Electrocardiograms 4. Predicting Resilience of Blood Groups Against the COVID-19 Delta Variant Using Machine Learning 5. A Key Role of Convolutional Neural Networks in Biomedical Imaging Applications 6. The Most Recent Developments and Applications of Smartphone-Based Devices in Biomedical and mHealth 7. Real-Time Health Monitoring Using IoT Sensors 8. IC Design: An Approach of Study in Biomedical and mHealth Care Applications 9. Experimental Setup and Analysis of Energy Harvesting Systems for a Low Power Biomedical Application: Lab on Chip Application of Impedance Micropump and Microfluidic Logic Gate 10. Analysis and Application of Power Amplifiers to Biomedical Instrumentation
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