000			04145nam a22004455i 4500
988			_aSpringer_Computer_2022
988			_aEbook_one2one
999			_c382945 _d382945 _x1
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003			ES-MaUEC
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008			221001s2022 sz | s |||| 0|eng d
020			_a9783030965693
024	7		_a10.1007/978-3-030-96569-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aR859.7.A78 _b2022 EB
245	0	0	_aArtificial Intelligence for Innovative Healthcare Informatics _cedited by Shabir Ahmad Parah, Mamoon Rashid, Vijayakumar Varadarajan
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (VI, 327 páginas) _b94 ilustraciones, 79 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
505	0		_aSection 1: Medical Image Analysis using Artificial Intelligence -- Use of Deep Learning in Biomedical Imaging.-Detection of Breast Cancer Masses in Mammogram Images with Watershed Segmentation and Machine Learning Approach -- Cloud-based Glaucoma Diagnosis in Medical Imaging using Machine Learning -- Leucocytic Cell Nucleus Identification using Boundary Cell Detection algorithm with Dilation and Erosion based Morphometry -- Effective Prediction of Autism Using Ensemble Method.-Section 2: Artificial Intelligence (AI) Classification Models for COVID-19 Pandemic.-Automatic Classification of COVID-19 infected patients using Convolution Neural Network Models.-AI-Based Deep Random Forest Ensemble Model for Prediction of COVID-19 and Pneumonia from Chest X-Ray Images -- Section 3: Use of AI-Enabled IoT in Healthcare -- Internet of Things and Artificial Intelligence in Biomedical Systems.-Role of IoT in Healthcare Sector for Monitoring Diabetic Patients -- Section 4: Applications of Artificial Intelligence in Healthcare -- Low-Rank Representation based approach for subspace segmentation and clustering of biomedical image patterns.-Performance Comparison of Imputation Methods for Heart Disease Prediction -- Ayurnano: A solution towards herbal therapeutics using Artificial Intelligence approach -- Artificial Intelligence in Biomedical Education -- The Emergence of Natural Language Processing (NLP) Techniques in Healthcare AI -- Prospects and Difficulties of Artificial Intelligence (AI) Implementations in Naturopathy.
520			_aThere are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier. However, in all these mentioned books, the challenges in Biomedical Imaging are solved in one dimension by use of any specific technology like Image Processing, Machine Learning or Computer Aided Systems. In this book, the book it has been attempted to bring all technologies related to computational analytics together and apply them on Biomedical Imaging.
650		7	_2embne _9421371 _aInteligencia artificial en medicina
700	1		_aParah, Shabir Ahmad _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aRashid, Mamoon _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aVaradarajan, Vijayakumar _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030965686
776	0	8	_iPrinted edition: _z9783030965709
776	0	8	_iPrinted edition: _z9783030965716
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-96569-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b10/2022 _dz _eIG _zSI