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Artificial intelligence techniques in breast cancer diagnosis and prognosis /

"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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Jain, Ashlesha
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore ; River Edge, NJ : World Scientific, ©2000.
Colección:Series in machine perception and artificial intelligence ; v. 39.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Artificial intelligence techniques in breast cancer diagnosis and prognosis /  |c editors, Ashlesha Jain [and others]. 
260 |a Singapore ;  |a River Edge, NJ :  |b World Scientific,  |c ©2000. 
300 |a 1 online resource (xvii, 330 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Series in machine perception and artificial intelligence ;  |v v. 39 
504 |a Includes bibliographical references and index. 
505 0 |a An 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 |a Print 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." 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Breast  |x Cancer  |x Diagnosis. 
650 0 |a Artificial intelligence. 
650 0 |a Artificial intelligence  |x Medical applications. 
650 1 2 |a Breast Neoplasms  |x diagnosis 
650 1 2 |a Breast Neoplasms  |x therapy 
650 2 2 |a Artificial Intelligence 
650 2 2 |a Diagnosis, Computer-Assisted  |x methods 
650 2 2 |a Therapy, Computer-Assisted  |x methods 
650 6 |a Sein  |x Cancer  |x Diagnostic. 
650 6 |a Intelligence artificielle en médecine. 
650 6 |a Intelligence artificielle. 
650 7 |a artificial intelligence.  |2 aat 
650 7 |a HEALTH & FITNESS  |x Diseases  |x Cancer.  |2 bisacsh 
650 7 |a MEDICAL  |x Oncology.  |2 bisacsh 
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650 7 |a Artificial intelligence.  |2 fast  |0 (OCoLC)fst00817247 
650 7 |a Breast  |x Cancer  |x Diagnosis.  |2 fast  |0 (OCoLC)fst00838268 
700 1 |a Jain, Ashlesha. 
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