LEADER 04950nam 2200649 450 001 9910736996903321 005 20231011233005.0 010 $a3-031-19752-6 024 7 $a10.1007/978-3-031-19752-9 035 $a(MiAaPQ)EBC7191140 035 $a(Au-PeEL)EBL7191140 035 $a(CKB)26089733900041 035 $a(DE-He213)978-3-031-19752-9 035 $a(PPN)268205043 035 $a(EXLCZ)9926089733900041 100 $a20230508h20232023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSystem design for epidemics using machine learning and deep learning /$fG.R. Kanagachidambaresan, Dinesh Bhatia, Dhilip Kumar, Animesh Mishra, editors 210 1$aCham, Switzerland :$cSpringer,$d[2023] 210 4$dİ2023 215 $a1 online resource (336 pages) 225 1 $aSignals and communication technology 311 08$aPrint version: Kanagachidambaresan, G. R. System Design for Epidemics Using Machine Learning and Deep Learning Cham : Springer International Publishing AG,c2023 9783031197512 327 $a1. 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. 330 $aThis book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time. 410 0$aSignals and communication technology. 606 $aArtificial intelligence$xMedical applications 606 $aDeep learning (Machine learning)$xTherapeutic use 606 $aEpidemics$xPrevention$xTechnological innovations 606 $aDeep learning (Machine learning) 606 $aEpidemics$xPrevention 606 $aDeep Learning 606 $aMachine Learning 606 $aEpidemics$xprevention & control 606 $aElectronic Data Processing$xmethods 615 0$aArtificial intelligence$xMedical applications. 615 0$aDeep learning (Machine learning)$xTherapeutic use. 615 0$aEpidemics$xPrevention$xTechnological innovations. 615 0$aDeep learning (Machine learning) 615 0$aEpidemics$xPrevention. 615 2$aDeep Learning. 615 2$aMachine Learning. 615 2$aEpidemics$xprevention & control. 615 2$aElectronic Data Processing$xmethods. 676 $a610.28563 702 $aKanagachidambaresan$b G. R. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910736996903321 996 $aSystem design for epidemics using machine learning and deep learning$93427812 997 $aUNINA