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008			220203s2022 sz | s |||| 0|eng d
020			_a9783030809287
024	7		_a10.1007/978-3-030-80928-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA304 _b2022 EB
245	1	0	_aMachine Learning for Critical Internet of Medical Things : _bApplications and Use Cases _cedited by Fadi Al-Turjman, Anand Nayyar
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (X, 261 páginas) _b89 ilustraciones, 79 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
505	0		_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.
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 physician's and doctor's 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.
988			_aSpringer_Computer_2022
650		7	_2embne _9421371 _aInteligencia artificial en medicina
700	1		_aAl-Turjman, Fadi _eeditor literario _0(orcid)0000-0001-6375-4123 _1https://orcid.org/0000-0001-6375-4123 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aNayyar, Anand _eeditor literario _0(orcid)0000-0002-9821-6146 _1https://orcid.org/0000-0002-9821-6146 _4edt _4http://id.loc.gov/vocabulary/relators/edt
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030809270
776	0	8	_iPrinted edition: _z9783030809294
776	0	8	_iPrinted edition: _z9783030809300
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-80928-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2022 _dz _eh _zSI