| Description |
1 online resource (247 p.) |
| Contents |
Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Foreword 1 -- FOREWORD 2 -- Foreword 2 -- Preface -- List of Contributors -- An SDN Based WBAN using Congestion Control Routing Algorithm with Energy Efficiency -- Poonguzhali S.1,*, Sathish Kumar D.2 and Immanuel Rajkumar R.1 -- INTRODUCTION -- Multiuser Detection -- Interference Cancellation -- EXISTING SYSTEM -- Exhaustive Search Method for Channel Estimation For OFDM -- DISADVANTAGES OF EXISTING SYSTEM -- PROPOSED METHODOLOGY -- RESULTS AND DISCUSSION -- CONCLUSION -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST |
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ACKNOWLEDGEMENTS -- REFERENCES -- COVID-19 -- Novel Short Term Prediction Methods -- Sanjay Raju1, Rishiikeshwer B.S.1, Aswin Shriram T.1, Brindha G.R.1,*, Santhi B.1,* and Bharathi N.2,* -- INTRODUCTION -- The Hurdles in Predicting COVID-19 -- Materials and Methods -- Novel Next Day Prediction Method -- Novel M Days Prediction Method -- The Mobile App -- RESULT AND DISCUSSION -- Next Day Prediction Analysis -- N-Days Deviation and M-Days Prediction Analysis -- CONCLUSION -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES |
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Intrusion Detection in IoT Based Health Monitoring Systems -- M.N. Ahil1,*, V. Vanitha1 and N. Rajathi1 -- INTRODUCTION -- RELATED WORKS -- Host-Based Intrusion Detection System (HIDS) -- Network Intrusion Detection System (NIDS) -- PROPOSED METHOD -- Data Collection -- Pre-Processing -- RESULTS AND DISCUSSION -- CONCLUSION -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Machine Learning Methods For Intelligent Health Care -- K. Kalaivani1,*, G. Valarmathi2, T. Kalaiselvi1 and V. Subashini2 -- INTRODUCTION -- APPLICATIONS OF MACHINE LEARNINGIN HEALTH CARE |
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Diagnosis of Diseases -- Drugdelivery and Manufacture -- Medical Imaging Diagnosis -- Personalized Medicine -- Machine Learning-Based Behavioral Modification -- Smart Health Records -- Clinical Trial and Research -- Crowd Sourced Data Collection -- Better Radiotherapy -- Outbreak Prediction -- Artificial Intelligence in Healthcare -- Clinical Analysis -- Machine Learning Approaches in Smart Health -- Machine Learning Methods in Smart Health -- CONCLUSION -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES |
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Multi-Factor Authentication Protocol Based on Electrocardiography Signals for a Mobile Cloud Computing Environment -- Silas L. Albuquerque1, Cristiano J. Miosso2, Adson F. da Rocha1 ,2 and Paulo R. L. Gondim1 ,* -- INTRODUCTION -- RELATED WORK -- Efficient Privacy-Aware Authentication Scheme for Mobile Cloud Computing Services -- An Enhanced Privacy-Aware Authentication Scheme for Distributed Mobile Cloud Computing Services -- CC Authentication Service Based on Keystroke Standards -- Efficient Authentication System Based on Several Factors For MCC |
| Summary |
This book focuses on recent developments in integrating AI, machine learning methods, medical image processing, advanced network security, and advanced antenna design techniques to implement practical Mobile Health (M-Health) systems. The editors bring together researchers and practitioners who address several developments in the field of M-Health. Chapters highlight intelligent healthcare IoT and Machine Learning based systems for personalized healthcare deli |
| Notes |
Description based upon print version of record |
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Comparison Between the Works Presented and this Work |
| Subject |
Medical technology.
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Telecommunication in medicine.
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Medical innovations.
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Medical Laboratory Science
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Medical innovations.
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Medical technology.
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Telecommunication in medicine.
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| Form |
Electronic book
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| Author |
R., Sivakumar
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Velev, Dimiter.
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Alhadidi, Basim, 1972-
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Vidhya, S
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| ISBN |
9815050591 |
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9789815050592 |
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