000			02526nam a2200373 i 4500
001			CR9781108872188
003			UkCbUP
005			20240807192828.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			191002s2022||||enk o ||1 0|eng|d
020			_a9781108872188 (ebook)
020			_z9781108836739 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aR858 _b.A768 2022
082	0	0	_a362.10285 _223/eng/20211202
245	0	0	_aArtificial intelligence for healthcare : _binterdisciplinary partnerships for analytics-driven improvements in a Post-COVID world / _cedited by Sze-chuan Suen, University of Southern California, David Scheinker, Stanford University, Eva Enns, University of Minnesota.
264		1	_aCambridge : _bCambridge University Press, _c2022.
300			_a1 online resource (x, 192 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 07 Apr 2022).
520			_aHealthcare has recently seen numerous exciting applications of artificial intelligence, industrial engineering, and operations research. This book, designed to be accessible to a diverse audience, provides an overview of interdisciplinary research partnerships that leverage AI, IE, and OR to tackle societal and operational problems in healthcare. The topics are drawn from a wide variety of disciplines, ranging from optimizing the location of AEDs for cardiac arrests to data mining for facilitating patient flow through a hospital. These applications highlight how engineering has contributed to medical knowledge, health system operations, and behavioral health. Chapter authors include medical doctors, policy-makers, social scientists, and engineers. Each chapter begins with a summary of the health care problem and engineering method. In these examples, researchers in public health, medicine, and social science as well as engineers will find a path to start interdisciplinary collaborations in health applications of AI/IE/OR.
650		0	_aMedical informatics.
650		0	_aMedical care _xData processing.
650		0	_aArtificial intelligence _xMedical applications.
700	1		_aSuen, Sze-chuan, _d1987- _eeditor.
700	1		_aScheinker, David, _eeditor.
700	1		_aEnns, Eva, _d1984- _eeditor.
776	0	8	_iPrint version: _z9781108836739
856	4	0	_uhttps://doi.org/10.1017/9781108872188
942			_2ddc _cEB
999			_c9224 _d9224