000			04016cam a2200565Ki 4500
001			9780429330131
003			FlBoTFG
005			20220711212410.0
006			m o d
007			cr |||||||||||
008			200917s2021 flua fob 000 0 eng d
040			_aOCoLC-P _beng _erda _epn _cOCoLC-P
020			_a9781000221787 _q(PDF ebook)
020			_a1000221784 _q(PDF ebook)
020			_a9780429330131 _q(electronic bk.)
020			_a0429330138 _q(electronic bk.)
020			_a9781000221831 _q(electronic bk. : Mobipocket)
020			_a1000221830 _q(electronic bk. : Mobipocket)
020			_a9781000221886 _q(electronic bk. : EPUB)
020			_a1000221881 _q(electronic bk. : EPUB)
035			_a(OCoLC)1227701522
035			_a(OCoLC-P)1227701522
050		4	_aR859.7.A78
072		7	_aCOM _x082000 _2bisacsh
072		7	_aCOM _x021030 _2bisacsh
072		7	_aCOM _x037000 _2bisacsh
072		7	_aUY _2bicssc
082	0	4	_a610.285631 _223
245	0	0	_aMachine learning for healthcare : _bhandling and managing data / _cedited by Rashmi Agrawal, Jyotir Moy Chatterjee, Abhishek Kumar, Pramod Singh Rathore, Dac-Nhuong Le.
264		1	_aBoca Raton : _bChapman & Hall/CRC, _c2021.
300			_a1 online resource : _billustrations (black and white)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
520			_aMachine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.
588			_aOCLC-licensed vendor bibliographic record.
650		0	_aMedical informatics. _94729
650		0	_aMachine learning. _91831
650		7	_aCOMPUTERS / Bioinformatics _2bisacsh _916044
650		7	_aCOMPUTERS / Database Management / Data Mining _2bisacsh _912290
650		7	_aCOMPUTERS / Machine Theory _2bisacsh _916193
700	1		_aAgrawal, Rashmi, _d1978- _eeditor. _910153
700	1		_aChatterjee, Jyotir Moy, _eeditor. _916194
700	1		_aKumar, Abhishek, _d1989- _eeditor. _916195
700	1		_aRathore, Pramod Singh, _d1988- _eeditor. _910152
700	1		_aLe, Dac-Nhuong, _d1983- _eeditor. _916196
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9780429330131
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942			_cEBK
999			_c71205 _d71205