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008			210130s2021 si | s |||| 0|eng d
020			_a9789811597350
024	7		_a10.1007/978-981-15-9735-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _erda _dES-MaUEC
050		4	_aQ342 _b2021 EB
245	0	0	_aHealth Informatics : _bA Computational Perspective in Healthcare _cedited by Ripon Patgiri, Anupam Biswas, Pinki Roy.
250			_aFirst edition 2021
264		1	_aSingapore _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (X, 377 páginas) _b196 ilustraciones, 147 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2
490	0		_aStudies in Computational Intelligence _x1860-949X _v932
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_a6G Communication Technology: A Vision on Intelligent Healthcare -- Deep Learning Based Medical Image Analysis Using Transfer Learning -- Wearable Internet of Things for Personalized Healthcare: Study of Trends and Latent Research -- Principal Component Analysis, Quantifying, and Filtering of Poincare Plots for Time Series Typal For E-Health -- Medical Image Generation Using Generative Adversarial Networks: A Review -- Comparative Analysis of Various Deep Learning Algorithms for Diabetic Retinopathy Images -- Software Design Specification and Analysis of Insulin Dose to Adaptive Carbohydrate Algorithm for Type 1 Diabetic Patients -- Iot Based Healthcare Monitoring System Using 5G Communication & Machine Learning Models -- Medical Image Classification Techniques and Analysis Using Deep Learning Networks: A Review.
520	3		_aThis book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help of computing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.
988			_aSpringer_Robotics_2021
650		7	_aInteligencia artificial _2embne _9413115
650		7	_aInformática médica _2embne _9421154
700	1		_aPatgiri, Ripon _eeditor literario _0(orcid)0000-0002-9899-9152 _1https://orcid.org/0000-0002-9899-9152 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aBiswas, Anupam _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aRoy, Pinki _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9789811597343
776	0	8	_iPrinted edition: _z9789811597367
776	0	8	_iPrinted edition: _z9789811597374
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-9735-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2021 _dz _eo _zSI