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_c115119 _d115119 _x1 |
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| 001 | 115119 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230102113650.0 | ||
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| 007 | cr nn nnnanaaa | ||
| 008 | 190710s2019 gw a o |||| 0|eng d | ||
| 020 | _a9783030118006 | ||
| 024 | 7 |
_a10.1007/978-3-030-11800-6 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC |
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| 050 | 4 |
_aR855.3 _b2019 EB |
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| 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 _c2019. |
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| 300 |
_a1 recurso en línea (XVI, 88 páginas) _b 35 ilustraciones, 23 ilustraciones a color. |
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| 347 |
_atext file _bPDF |
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| 490 | 0 |
_aAdvances in Predictive Preventive and Personalised Medicine _x2211-3495 _v10 |
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| 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. | |
| 650 | 7 |
_aTecnología médica _2embne _9150466 |
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| 650 | 7 |
_aInformática médica _2embne _9421154 |
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| 700 | 1 |
_aChaari, Lotfi _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 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 Madrid) |
| 942 |
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| 988 | _aSpringer_Medicine_2019 | ||
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_aSí _cm _dz _feng _ggw _h0 _b11/2019 _eh _zSI |
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