MARC record from Internet Archive

LEADER: 05507cam 2200841 a 4500
001 ocn827945004
003 OCoLC
005 20220513135040.0
008 130218s2000 si a ob 001 0 eng d
006 m o d
007 cr cnu---unuuu
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019 $a854974242$a1086440895
020 $a9789812792488$q(electronic bk.)
020 $a9812792481$q(electronic bk.)
020 $z9789810243746
020 $z981024374X
035 $a(OCoLC)827945004$z(OCoLC)854974242$z(OCoLC)1086440895
050 4 $aRC280.B8$bA78 2000eb
060 4 $a2001 H-302
060 4 $aWP 870$bA791 2000
072 7 $aHEA$x039030$2bisacsh
072 7 $aMED$x062000$2bisacsh
082 04 $a616.99449$222
245 00 $aArtificial intelligence techniques in breast cancer diagnosis and prognosis /$ceditors, Ashlesha Jain [and others].
260 $aSingapore ;$aRiver Edge, NJ :$bWorld Scientific,$c©2000.
300 $a1 online resource (xvii, 330 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aSeries in machine perception and artificial intelligence ;$vv. 39
504 $aIncludes bibliographical references and index.
505 0 $aAn introduction to breast cancer diagnosis, prognosis, and Artificial Intelligence / N. Harbeck [and others] -- Automatic image feature extraction for diagnosis and prognosis of breast cancer / M.J. Bottema, G.N. Lee, and S. Lu -- Decision support in breast cancer: recent advances in prognostic and predictive techniques / R. Kates [and others] -- MammoNet: a Baynesian network diagnosing breast cancer / L.M. Roberts -- Predicting prognosis and treatment response in breast cancer patients / M.G Daidone and D. Coradini -- Computer-aided breast cancer diagnosis / H.-P Chan, N. Petrick, and B. Sahiner -- Which decision support technologies are appropriate for the cytodiagnosis of breast cancer? / S.S Cross [and others] -- Xcyt: a system for remote cytological diagnosis and prognosis of breast cancer / W.N. Street.
588 0 $aPrint version record.
520 $a"The main aim of this book is to present a sample of recent research on the application of novel artificial intelligence paradigms to the diagnosis and prognosis of breast cancer. These paradigms include neural networks, fuzzy logic and evolutionary computing. Artificial intelligence techniques offer advantages -- such as adaptation, fault tolerance, learning and human-like behavior -- over conventional computing techniques. The idea is to combine the pathological, intelligent and statistical approaches to enable simple and accurate diagnosis and prognosis. This book is the first of its kind on the topic of artificial intelligence in breast cancer. It presents the applications of artificial intelligence in breast cancer diagnosis and prognosis, and includes state-of-the-art concepts in the field. It contains contributions from Australia, Germany, Italy, UK and the USA."
650 0 $aBreast$xCancer$xDiagnosis.
650 0 $aArtificial intelligence.
650 0 $aArtificial intelligence$xMedical applications.
650 12 $aBreast Neoplasms$xdiagnosis
650 12 $aBreast Neoplasms$xtherapy
650 22 $aArtificial Intelligence
650 22 $aDiagnosis, Computer-Assisted$xmethods
650 22 $aTherapy, Computer-Assisted$xmethods
650 6 $aSein$xCancer$xDiagnostic.
650 6 $aIntelligence artificielle en médecine.
650 6 $aIntelligence artificielle.
650 7 $aartificial intelligence.$2aat
650 7 $aHEALTH & FITNESS$xDiseases$xCancer.$2bisacsh
650 7 $aMEDICAL$xOncology.$2bisacsh
650 7 $aBreast$xCancer$xDiagnosis.$2fast$0(OCoLC)fst00838268
655 4 $aElectronic books.
700 1 $aJain, Ashlesha.
776 08 $iPrint version:$tArtificial intelligence techniques in breast cancer diagnosis and prognosis.$dSingapore ; River Edge, NJ : World Scientific, ©2000$z9789810243746$w(OCoLC)46405680
830 0 $aSeries in machine perception and artificial intelligence ;$vv. 39.
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856 40 $uhttp://www.worldscientific.com/worldscibooks/10.1142/4484#t=toc$zClick for access to ebook
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