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System Design for Epidemics Using Machine Learning and Deep Learning de G. R. Kanagachidambaresan

System Design for Epidemics Using Machine Learning and Deep Learning: Signals and Communication Technology

Editat de G. R. Kanagachidambaresan, Dinesh Bhatia, Dhilip Kumar, Animesh Mishra
en Limba Engleză Paperback – 2 feb 2024
This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.
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Specificații

ISBN-13: 9783031197543
ISBN-10: 3031197542
Pagini: 325
Ilustrații: XXII, 325 p. 164 illus., 130 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2023
Editura: Springer International Publishing
Colecția Springer
Seria Signals and Communication Technology

Locul publicării:Cham, Switzerland

Cuprins

1. Pandemic effect of COVID-19: Identification, Present scenario and preventive measures using Machine learning model..- 2. A Comprehensive Review of the Smart Health Records to prevent Pandemic.- 3. Automation of COVID-19 Disease Diagnosis from Radiograph.- 4. Applications of Artificial Intelligence in the attainment of Sustainable Development Goals.- 5. A Novel Model for IoT Blockchain Assurance Based Compliance to COVID Quarantine.- 6. DEEP LEARNING BASED CONVOLUTIONALNEURAL NETWORK WITH RANDOM FOREST APPROACH FOR MRI BRAIN TUMOUR SEGMENTATION .- 7. Expert systems for improving the effectiveness of remote health monitoring in Covid-19 Pandemic - A Critical Review.- 8. Artificial Intelligence-based predictive tools for Life-threatening diseases.- 9. Deep Convolutional Generative Adversarial Network for Metastatic Tissue Diagnosis in Lymph Node Section.- 10. Transformation in Health Sector during Pandemic by Photonics Devices .- 11. DIAGNOSIS OF COVID-19 FROM CT IMAGES AND RESPIRATORYSOUND SIGNALS USING DEEP LEARNING STRATEGIES.- 12. The Role of Edge Computing in Pandemic and Epidemic Situations with its Solutions.- 13. Advances and application of Artificial Intelligence and Machine learning in the field of cardiovascular diseases and its role during the Pandemic condition.- 14. Effective Health Screening and Prompt Vaccination to Counter the Spread of Covid-19 and Minimize its Adverse Effects.- 15. CROWD DENSITY ESTIMATION USING NEURAL NETWORK FOR COVID’19 AND FUTURE PANDEMICS.- 16. “Role of digital healthcare in rehabilitation during pandemic”.- 17. AN EPIDEMIC OF NEURODEGENERATIVE DISEASE ANALYSIS USING MACHINE LEARNING TECHNIQUES.- 18. Covid-19 Growth Curve Forecasting for India using Deep Learning Techniques.

Notă biografică

Dr. G. R. Kanagachidambaresan received his B.E degree in Electrical and Electronics Engineering from Anna University in 2010 and M.E. Pervasive Computing Technologies in Anna University in 2012. He has completed his Ph.D. in Anna University Chennai in 2017. He is currently an Associate Professor, Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology. He is also working as Visiting professor in Department of Institute of Intelligent Systems, University of Johannesburg, South Africa. His main research interest includes Internet of Things and expert systems design . He has published several reputed articles and undertaken several consultancy activities for leading MNC companies. He has also guest edited several special issue volumes and books in SPRINGER and serving as editorial review board members for peer reviewed journals. He is presently working on several Govt sponsored research projects like ISRO, DBT and DST. He is an ASEM-DUO fellowship,He has successfully edited several books in EAI springer. He is presently Editor in chief for Next Generation Computer and Communication Engineering series Wiley.
Dr. Dinesh Bhatia pursued his PhD in Biomechanics and Rehabilitation Engineering from MNNIT, Allahabad, India in 2010 with Bachelor’s (2002) and Master’s degree (2004) in Biomedical Engineering from Mumbai University. He completed his MBA (Dual Specialization) from IMT Ghaziabad in 2007. He is currently working as Associate Professor in the Department of Biomedical Engineering, North Eastern Hill University (NEHU), Shillong, Meghalaya, India He is the recipient of the “Young Scientist Award (BOYSCAST 2011-12)” by Government of India to pursue research in osteoarthritis (OA) for one year at Adaptive Neural Systems Laboratory, Biomedical Engineering Department, Florida International University, Miami, Florida, USA where he was leading a multidisciplinary team of researchers. He is also the recipient of “INAE fellowshipaward” in 2011 by Indian National Academy of Engineering. He was selected as one of the twelve young Biomedical scientists by the Indian Council of Medical Research (ICMR), Govt. of India to pursue research fellowship (2014-15) in the field of sensory prosthetics at University of Glasgow, Scotland, UK. He has attended Biomechanics and Human Gait training at Munich, Germany in March, 2017 and training of use of Neuro-diagnostics equipment(s) at Ivanovo, Russia in September, 2017. He delivered an Invited Talk on Gait and Osteoarthritis in Kaula Lampur, Malaysia in August, 2018. He has several research papers in reputed journals, conference, seminars and symposia with teaching and research experience of more than seventeen (17) years. He is invited panel member of several professional bodies, editorial boards, committees, societies and forums. He has worked on various funded projects on physically challenged, disabled and paralyzed persons and few projects are still on-going. He has published 09 books and 21 books chapters till date and supervised several UG, PG and doctoral students. His research focuses on understanding muscle mechanics, joint kinematics and dynamics involved in performing locomotion and routine tasks and undermining it effects during an injury or disease. His areas of interest are medical instrumentation, biomechanics and rehabilitation engineering, medical informatics, signal and image processing, marketing and international business.
Dr. V. Dhilip Kumar, He was awarded PhD at North Eastern Hill University (A Central University of INDIA) in 2017. Presently, he is working as an associate professor in the Department of computer science and engineering at Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai. He has more than 10 + years’ experience of teaching as well as research. He did his B.Tech Information Technology and M.E. Computer science engineering under Anna University, Chennai. He has published various international journals and international conferences in the field of vehicular communication and Machine Learning. He is an editorial board member and reviewer of various international journals and conferences in reputed publishers like Springer, IEEE, Elsevier, Wiley etc. His area of interest is Vehicular communication, Soft Computing techniques, Internet of things, Machine learning etc. He is presently working on projects related to artificial intelligence for healthcare and automations. Dr. Animesh Mishra, Professor, Department of Cardiology, NEIGRIHMS (An autonomous institute, Under ministry of Health & Family Welfare, Government of India). Dr. Animesh Mishra has completed his D.M in Cardiology in MAMC Delhi University. He has completed his MD in internal Medicine from Institute of Medical Sciences, BHU Varanasi. He is having more than 25 years of Professional experience. He has published in several reputed journals.

Textul de pe ultima copertă

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

Caracteristici

Provides artificial intelligence and machine learning solutions Addresses technological challenges faced while realizing the potential Relevant to researchers