MARC 主機 00000cam  2200565Ia 4500 
001    ocn162131472 
003    OCoLC 
005    20110615082927.0 
006    m        d         
007    cr cn||||||||| 
008    070802s2007    ne a    ob    001 0 eng d 
020    9780444528551 
020    0444528555 
035    (OCoLC)162131472 
037    134303:134431|bElsevier Science & Technology|nhttp://
       www.sciencedirect.com 
040    OPELS|cOPELS|dBAKER|dOPELS 
049    TEFA 
050 14 RC270|b.O98 2007eb 
060 14 2007 B-597 
060 14 QZ 241|bO94 2007 
082 04 616.99/4075|222 
245 00 Outcome prediction in cancer|h[electronic resource] /
       |ceditors, Azzam F.G. Taktak and Anthony C. Fisher 
250    1st ed 
260    Amsterdam ;|aBoston :|bElsevier,|cc2007 
300    xx, 461 p. :|bill. ;|c25 cm 
504    Includes bibliographical references and index 
505 0  Section 1 The Clinical Problem. -- THE PREDICTIVE VALUE OF
       DETAILED HISTOLOGICAL STAGING OF SURGICAL RESECTION 
       SPECIMENS IN ORAL CANCER -- Chapter 1: The predictive 
       value of detailed histological staging of surgical 
       resection specimens in oral cancer. -- J. Woolgar -- 
       Liverpool Dental School, UK -- Chapter 2: Survival after 
       Treatment of Intraocular Melanoma. -- B.E. Damato, A.F.G. 
       Taktak, -- Royal Liverpool University Hospital, UK -- 
       Chapter 3: Recent developments in relative survival 
       analysis. -- T. Hakulinen, T.A. Dyba, -- Finnish Cancer 
       Registry -- Section 2 Biological and Genetic Factors -- 
       Chapter 4: Environmental and genetic risk factors of lung 
       cancer. -- A. Cassidy, J.K. Field, -- University of 
       Liverpool, UK -- Chapter 5: Chaos, cancer, the cellular 
       operating system and the prediction of survival in head 
       and neck cancer. -- A.S. Jones, -- University Hospital 
       Aintree, UK -- Section 3 Mathematical Background of 
       Prognostic Models -- Chapter 6: Flexible hazard modelling 
       for outcome prediction in cancer - perspectives for the 
       use of bioinformatics knowledge. -- E.Biganzoli1, P. 
       Boracchi2 -- 1 Istituto Nazionale per lo Studio e la Cura 
       dei Tumori, Milano, Italy -- 2 Universỉt degli Studi di 
       Milano, Milano, Italy -- Chapter 7: Information geometry 
       for survival analysis and feature selection by neural 
       networks. -- A. Eleuteri 1,2, R. Tagliaferri 3,4, L. 
       Milano 1,2, M. De Laurentiis 1 -- 1Universỉt di Napoli, 
       Italy -- 2INFN sez. Napoli, Italy -- 3Università di 
       Salerno, Italy -- 4INFN sez. distaccata di Salerno, Italy 
       -- Chapter 8: Artificial neural networks used in the 
       survival analysis of breast cancer patients: A node 
       negative study. -- C.T.C. Arsene, P.J. Lisboa, -- 
       Liverpool John Moores University, UK -- Section 4 
       Application of Machine Learning Methods -- Chapter 9: The 
       use of artificial neural networks for the diagnosis and 
       estimation of prognosis in cancer patients. -- A. 
       Marchevsky, -- Cedars-Sinai Medical Center, Los Angeles, 
       USA -- Chapter 10: Machine learning contribution to solve 
       prognosis medical problems. -- F. Baronti, A. Micheli, A. 
       Passaro, A.Starita, -- University of Pisa, Italy -- 
       Chapter 11: Classification of brain tumours by pattern 
       recognition of Magnetic Resonance Imaging and 
       Spectroscopic data. -- A. Devos1, S. Van Huffel1 A.W. 
       Simonetti1, M. van der Graaf2, A. Heerschap2, L.M.C. 
       Buydens3 -- 1Katholieke Universiteit Leuven, Belgium -- 
       2University Nijmegen Medical Centre, The Netherlands -- 
       3Radboud University Nijmegen, The Netherlands -- -- 
       Chapter 12: Towards automatic risk analysis for hereditary
       non-polyposis colorectal cancer based on pedigree data. --
       M. Kokuer1, R.N.G. Naguib1, P. Jancovic2, H.B. 
       Younghusband3, R. Green3 -- 1Coventry University, UK -- 
       2University of Birmingham, UK -- 3University of 
       Newfoundland, Canada -- Chapter 13: The impact of 
       microarray technology in brain cancer. -- M. Kounelakis1, 
       M. Zervakis1, X. Kotsiakis2 -- 1Technical University of 
       Crete, GREECE -- 2District Hospital of Chania, GREECE -- 
       Section 5 Dissemination of Information -- Chapter 14: The 
       web and the new generation of medical information. -- J.M.
       Fonseca, A.D. Mora, P. Barroso -- University of Lisbon, 
       Portugal -- Chapter 15: Geoconda: a web environment for 
       multi-centre research. -- C. Setzkorn, A.F.G. Taktak, B.E.
       Damato -- Royal Liverpool University Hospital, Liverpool, 
       UK -- Chapter 16: The development and execution of medical
       prediction models. -- M.W. Kattan1, M. ̲Gnen2, P.T. 
       Scardino2 -- 1The Cleveland Clinic Fondation, Cleveland, 
       USA -- 2Memorial Sloan-Kettering Cancer Center, New York, 
       USA 
505 0  The predictive value of detailed histological staging of 
       surgical resection specimens in oral cancer -- Survival 
       after treatment of intraocular melanoma -- Recent 
       developments in relative survival analysis -- 
       Environmental and genetic risk factors of lung cancer -- 
       Chaos, cancer, the cellular operating system and the 
       prediction of survival in head and neck cancer -- Flexible
       hazard modelling for outcome prediction in cancer: 
       perspectives for the use of bioinformatics knowledge -- 
       Information geometry for survival analysis and feature 
       selection by neural networks -- Artificial neural networks
       used in the survival analysis of breast cancer patients: a
       node-negative study -- The use of artificial neural 
       networks for the diagnosis and estimation of prognosis in 
       cancer patients -- Machine learning contribution to solve 
       prognostic medical problems -- Classification of brain 
       tumors by pattern recognition of magnetic resonance 
       imaging and spectroscopic data -- Towards automatic risk 
       analysis for hereditary non-polyposis colorectal cancer 
       based on pedigree data -- The impact of microarray 
       technology in brain cancer -- The web and the new 
       generation of medical information systems -- Geoconda: a 
       web environment for multi-centre research -- The 
       development and execution of medical prediction models 
520    This book is organized into 4 sections, each looking at 
       the question of outcome prediction in cancer from a 
       different angle. The first section describes the clinical 
       problem and some of the predicaments that clinicians face 
       in dealing with cancer. Amongst issues discussed in this 
       section are the TNM staging, accepted methods for survival
       analysis and competing risks. The second section describes
       the biological and genetic markers and the ̥rle of 
       bioinformatics. Understanding of the genetic and 
       environmental basis of cancers will help in identifying 
       high-risk populations and developing effective prevention 
       and early detection strategies. The third section provides
       technical details of mathematical analysis behind survival
       prediction backed up by examples from various types of 
       cancers. The fourth section describes a number of machine 
       learning methods which have been applied to decision 
       support in cancer. The final section describes how 
       information is shared within the scientific and medical 
       communities and with the general population using 
       information technology and the World Wide Web. * 
       Applications cover 8 types of cancer including brain, eye,
       mouth, head and neck, breast, lungs, colon and prostate * 
       Include contributions from authors in 5 different 
       disciplines * Provides a valuable educational tool for 
       medical informatics 
533    Electronic reproduction.|bAmsterdam :|cElsevier Science & 
       Technology,|d2007.|nMode of access: World Wide Web.
       |nSystem requirements: Web browser.|nTitle from title 
       screen (viewed on July 25, 2007).|nAccess may be 
       restricted to users at subscribing institutions 
590    Elsevier 
650  0 Cancer|xDiagnosis 
650  0 Cancer|xPrognosis 
650  0 Neural networks (Computer science) 
650  0 Survival analysis (Biometry) 
650 12 Neoplasms|xdiagnosis 
650 12 Prognosis 
650 22 Decision Support Systems, Clinical 
650 22 Neural Networks (Computer) 
650 22 Survival Analysis 
655  7 Electronic books.|2local 
700 1  Taktak, Azzam F. G 
700 1  Fisher, Anthony C.,|cDr 
710 2  ScienceDirect (Online service) 
776 1  |cOriginal|z9780444528551|z0444528555|w(OCoLC)77482420 
856 40 |3ScienceDirect|uhttp://www.sciencedirect.com/science/book
       /9780444528551|zeBook(Elsevier)