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008			180823s2019 gw a o |||| 0|eng d
020			_a9783319986753
024	7		_a10.1007/978-3-319-98675-3 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aQ325.5 _b2019 EB
100	1		_aPham, Thuy T. _eautor _9670818
245	1	0	_aApplying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings _cby Thuy T. Pham
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019
300			_a1 recurso en línea (XV, 107 páginas) _b35 ilustraciones, 32 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
490	0		_aSpringer Theses Recognizing Outstanding Ph.D. Research _x2190-5053
505	0		_aIntroduction -- Background -- Algorithms -- Point Anomaly Detection: Application to Freezing of Gait Monitoring -- Collective Anomaly Detection: Application to Respiratory Artefact Removals -- Spike Sorting: Application to Motor Unit Action Potential Discrimination -- Conclusion .
520	3		_aThis book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.
650		7	_2embne _aAprendizaje automático _9166090
650		7	_2embne _9421371 _aInteligencia artificial en medicina
650		7	_2embne _aInformática médica _9421154
776	0	8	_iPrinted edition: _z9783030075187
776	0	8	_iPrinted edition: _z9783319986746
776	0	8	_iPrinted edition: _z9783319986760
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-98675-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aPrimersemestre_2019_Engineering
998			_aSI _cm _dz _feng _ggw _h0 _b09/2019 _eel _zSI