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020			_a9783030118006
024	7		_a10.1007/978-3-030-11800-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-VaUE
050		4	_aR855.3 _b.D54 2019 EB
245	0	0	_aDigital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine _cedited by Lotfi Chaari.
250			_a1st ed. 2019.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019.
300			_a1 recurso en línea (XVI, 88 páginas) _b 35 ilustraciones, 23 ilustraciones a color
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aAdvances in Predictive Preventive and Personalised Medicine _x2211-3495 _v10
490	0		_aMedicine (Springer-11650)
505	0		_aPreface -- Introduction -- Seizure onset detection in EEG signals based on entropy from generalized Gaussian PDF modeling and ensemble bagging classifer -- Arti_cial Neuroplasticity by Deep Learning Reconstruc-tion Signal to Reconnect Motion signal for Spinal Cord -- Improved Massive MIMO Cylindrical Adaptive Anten-na Array -- Multifractal Analysis With Lacunarity for Microcalci_cations Segmentation -- Consolidated Clinical Document Architecture: Analysis and Evaluation to Support the Interoperability of Tunisian Health -- Bayesian compressed sensing for IoT: application to EEG recording -- Patients Strati_cation in Imbalanced Datasets: A Roadmap -- Real-Time Driver Fatigue Monitoring with Dynamic Bayesian Network Model -- Epileptic seizure detection using a Convolutional Neural Network -- Index.
520	3		_aThis collection, entitled « Digital Health for Predictive, Preventive, Personalized and Participatory Medicine» contains the proceedings of the first International conference on digital health technologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.
988			_aSegundosemestre_2019_Medicine
650		7	_aTecnología médica _9150466 _2embne
650		7	_aInformática médica _2embne _9421154
700	1		_aChaari, Lotfi _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service) _9106937
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030117993
776	0	8	_iPrinted edition: _z9783030118013
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-11800-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
998			_db _feng _ggw _h0 _zSI