04950nam 2200649 450 991073699690332120231011233005.03-031-19752-610.1007/978-3-031-19752-9(MiAaPQ)EBC7191140(Au-PeEL)EBL7191140(CKB)26089733900041(DE-He213)978-3-031-19752-9(PPN)268205043(EXLCZ)992608973390004120230508h20232023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierSystem design for epidemics using machine learning and deep learning /G.R. Kanagachidambaresan, Dinesh Bhatia, Dhilip Kumar, Animesh Mishra, editorsCham, Switzerland :Springer,[2023]©20231 online resource (336 pages)Signals and communication technologyPrint version: Kanagachidambaresan, G. R. System Design for Epidemics Using Machine Learning and Deep Learning Cham : Springer International Publishing AG,c2023 9783031197512 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 RESPIRATORY SOUND 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.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.Signals and communication technology.Artificial intelligenceMedical applicationsDeep learning (Machine learning)Therapeutic useEpidemicsPreventionTechnological innovationsDeep learning (Machine learning)EpidemicsPreventionDeep LearningMachine LearningEpidemicsprevention & controlElectronic Data ProcessingmethodsArtificial intelligenceMedical applications.Deep learning (Machine learning)Therapeutic use.EpidemicsPreventionTechnological innovations.Deep learning (Machine learning)EpidemicsPrevention.Deep Learning.Machine Learning.Epidemicsprevention & control.Electronic Data Processingmethods.610.28563Kanagachidambaresan G. R. MiAaPQMiAaPQMiAaPQBOOK9910736996903321System design for epidemics using machine learning and deep learning3427812UNINA