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001454463 001__ 1454463
001454463 003__ OCoLC
001454463 005__ 20230314003520.0
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001454463 020__ $$a9783031197529$$q(electronic bk.)
001454463 020__ $$a3031197526$$q(electronic bk.)
001454463 020__ $$z9783031197512
001454463 020__ $$z3031197518
001454463 0247_ $$a10.1007/978-3-031-19752-9$$2doi
001454463 035__ $$aSP(OCoLC)1369203136
001454463 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP
001454463 049__ $$aISEA
001454463 050_4 $$aR859.7.A78
001454463 08204 $$a610.285/63$$223/eng/20230208
001454463 24500 $$aSystem design for epidemics using machine learning and deep learning /$$cG.R. Kanagachidambaresan, Dinesh Bhatia, Dhilip Kumar, Animesh Mishra, editors.
001454463 264_1 $$aCham :$$bSpringer,$$c[2023]
001454463 264_4 $$c©2023
001454463 300__ $$a1 online resource (xxii, 325 pages) :$$billustrations (chiefly color).
001454463 336__ $$atext$$btxt$$2rdacontent
001454463 337__ $$acomputer$$bc$$2rdamedia
001454463 338__ $$aonline resource$$bcr$$2rdacarrier
001454463 4901_ $$aSignals and communication technology
001454463 504__ $$aIncludes bibliographical references and index.
001454463 5050_ $$a1. Pandemic effect of COVID-19: Identification, Present scenario and preventive measures using Machine learning model. -- 2. A Comprehensive Review of the Smart Health Records to prevent Pandemic -- 3. Automation of COVID-19 Disease Diagnosis from Radiograph -- 4. Applications of Artificial Intelligence in the attainment of Sustainable Development Goals -- 5. A Novel Model for IoT Blockchain Assurance Based Compliance to COVID Quarantine -- 6. DEEP LEARNING BASED CONVOLUTIONALNEURAL NETWORK WITH RANDOM FOREST APPROACH FOR MRI BRAIN TUMOUR SEGMENTATION -- 7. Expert systems for improving the effectiveness of remote health monitoring in Covid-19 Pandemic - A Critical Review -- 8. Artificial Intelligence-based predictive tools for Life-threatening diseases -- 9. Deep Convolutional Generative Adversarial Network for Metastatic Tissue Diagnosis in Lymph Node Section -- 10. Transformation in Health Sector during Pandemic by Photonics Devices -- 11. DIAGNOSIS OF COVID-19 FROM CT IMAGES AND RESPIRATORY SOUND SIGNALS USING DEEP LEARNING STRATEGIES -- 12. The Role of Edge Computing in Pandemic and Epidemic Situations with its Solutions -- 13. Advances and application of Artificial Intelligence and Machine learning in the field of cardiovascular diseases and its role during the Pandemic condition -- 14. Effective Health Screening and Prompt Vaccination to Counter the Spread of Covid-19 and Minimize its Adverse Effects -- 15. CROWD DENSITY ESTIMATION USING NEURAL NETWORK FOR COVID19 AND FUTURE PANDEMICS -- 16. Role of digital healthcare in rehabilitation during pandemic -- 17. AN EPIDEMIC OF NEURODEGENERATIVE DISEASE ANALYSIS USING MACHINE LEARNING TECHNIQUES -- 18. Covid-19 Growth Curve Forecasting for India using Deep Learning Techniques.
001454463 506__ $$aAccess limited to authorized users.
001454463 520__ $$aThis book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.
001454463 588__ $$aDescription based on print version record.
001454463 650_0 $$aArtificial intelligence$$xMedical applications.
001454463 650_0 $$aDeep learning (Machine learning)$$xTherapeutic use.
001454463 650_0 $$aEpidemics$$xPrevention$$xTechnological innovations.
001454463 655_0 $$aElectronic books.
001454463 7001_ $$aKanagachidambaresan, G. R.,$$d1988-$$eeditor.$$1https://isni.org/isni/0000000495627235
001454463 7001_ $$aBhatia, Dinesh Kumar,$$d1964-$$eeditor.$$1https://isni.org/isni/0000000045456176
001454463 7001_ $$aKumar, Dhilip,$$eeditor.
001454463 7001_ $$aMishra, Animesh,$$eeditor.
001454463 77608 $$iPrint version:$$tSystem design for epidemics using machine learning and deep learning.$$dCham : Springer, 2023$$z9783031197512$$w(OCoLC)1356960108
001454463 830_0 $$aSignals and communication technology.
001454463 852__ $$bebk
001454463 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-19752-9$$zOnline Access$$91397441.1
001454463 909CO $$ooai:library.usi.edu:1454463$$pGLOBAL_SET
001454463 980__ $$aBIB
001454463 980__ $$aEBOOK
001454463 982__ $$aEbook
001454463 983__ $$aOnline
001454463 994__ $$a92$$bISE