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008			210724s2021 sz | s |||| 0|eng d
020			_a9783030718817
024	7		_a10.1007/978-3-030-71881-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aRK51 _b2021 EB
245	0	0	_aMachine Learning in Dentistry _cedited by Ching-Chang Ko, Dinggang Shen, Li Wang
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (X, 188 páginas) _b90 ilustraciones, 76 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
505	0		_aMachine Learning for Dental Imaging: Machine Learning for CBCT Segmentation of Craniofacial 3D Image -- Machine Learning for Automatic Landmark Detection of 3D Imaging -- Machine Learning for Generating Dental CT from Magnetic Resonance Imaging (MRI) -- Machine Learning for 2D Dynamic Facial Photographs. Machine Learning for Oral Diagnosis and Treatment: Machine Learning for Orthodontic Diagnosis and Treatment Planning -- Machine Learning for Diagnosis of Periodontal Diseases -- Machine Learning for Oral Microbiome -- Machine Learning for Characterization of Craniofacial Anomaly -- Machine Learning for Orthognathic Surgery -- Machine Learning for Bone Tissue Engineering. Machine Learning and Dental Designs: Machine Learning for Orthodontic CAD/CAM Technologies -- Machine Learning for Design of Dental Implants -- Machine Learning for Optimization of Dental Material Processing. Machine Learning Supporting Dental Research: Machine Learning for Data Mining in Teledentistry -- Machine Learning for Evidence-Based Literature Search -- Machine Learning in Genetics and Genomics -- Machine Learning and Finite Element Modeling.
520			_aThis book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to "learn", for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for all dental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.
988			_aSpringer_Medicine_2021
650		7	_2embne _aOdontología _9138473
650		7	_2embne _9166090 _aAprendizaje automático
700	1		_aKo, Ching-Chang _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aShen, Dinggang _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aWang, Li _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030718800
776	0	8	_iPrinted edition: _z9783030718824
776	0	8	_iPrinted edition: _z9783030718831
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-71881-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2022 _dz _eb _zSI