001444258 000__ 04318cam\a2200577Ii\4500
001444258 001__ 1444258
001444258 003__ OCoLC
001444258 005__ 20230310003700.0
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001444258 007__ cr\un\nnnunnun
001444258 008__ 220206s2022\\\\sz\a\\\\o\\\\\001\0\eng\d
001444258 019__ $$a1295379527$$a1295405503$$a1296424632$$a1296666561
001444258 020__ $$a9783030809287$$q(electronic bk.)
001444258 020__ $$a3030809285$$q(electronic bk.)
001444258 020__ $$z9783030809270
001444258 020__ $$z3030809277
001444258 0247_ $$a10.1007/978-3-030-80928-7$$2doi
001444258 035__ $$aSP(OCoLC)1295352635
001444258 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dN$T$$dGW5XE$$dDKU$$dEBLCP$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCQ
001444258 049__ $$aISEA
001444258 050_4 $$aR859.7.A78$$bM33 2022
001444258 08204 $$a610.285/63$$223
001444258 24500 $$aMachine learning for critical Internet of medical things :$$bapplications and use cases /$$cFadi Al-Turjman, Anand Nayyar, editors.
001444258 264_1 $$aCham :$$bSpringer,$$c[2022]
001444258 264_4 $$c©2022
001444258 300__ $$a1 online resource :$$billustrations (chiefly color)
001444258 336__ $$atext$$btxt$$2rdacontent
001444258 337__ $$acomputer$$bc$$2rdamedia
001444258 338__ $$aonline resource$$bcr$$2rdacarrier
001444258 347__ $$atext file$$bPDF$$2rda
001444258 500__ $$aIncludes index.
001444258 5050_ $$aIntroduction -- An Introduction to Basic Concepts on Machine Learning, its architecture and framework -- Machine Learning Models and techniques -- Diseases diagnosis and prediction using Machine Learning -- Machine learning for Mobile/e-health, Tele-medical and Remote healthcare networks -- Machine learning in biomedical, Neuro-critical and medical image processing field -- AI, Deep learning and machine learning enabled connected health informatics -- Machine learning enabled smart healthcare system -- Machine learning based efficient health monitoring systems -- Machine learning case study for virus disease Ebola, COVID-19 consequences -- CASE Study: Machine Learning in Medical domain for Cervical Cancer -- Use cases and applications of machine learning in medical domain -- Conclusion.
001444258 506__ $$aAccess limited to authorized users.
001444258 520__ $$aThis book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physicians and doctors medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system. Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas; Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer; Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.
001444258 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 17, 2022).
001444258 650_0 $$aMachine learning.
001444258 650_0 $$aArtificial intelligence$$xMedical applications.
001444258 650_0 $$aInternet of things.
001444258 650_6 $$aApprentissage automatique.
001444258 650_6 $$aIntelligence artificielle en médecine.
001444258 650_6 $$aInternet des objets.
001444258 655_0 $$aElectronic books.
001444258 7001_ $$aAl-Turjman, Fadi,$$eeditor.
001444258 7001_ $$aNayyar, Anand,$$eeditor.
001444258 77608 $$iPrint version:$$z3030809277$$z9783030809270$$w(OCoLC)1256253915
001444258 852__ $$bebk
001444258 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-80928-7$$zOnline Access$$91397441.1
001444258 909CO $$ooai:library.usi.edu:1444258$$pGLOBAL_SET
001444258 980__ $$aBIB
001444258 980__ $$aEBOOK
001444258 982__ $$aEbook
001444258 983__ $$aOnline
001444258 994__ $$a92$$bISE