UID:
almahu_9948234162202882
Format:
1 online resource (ix, 368 pages) :
,
digital, PDF file(s).
ISBN:
9780511543494 (ebook)
Content:
Artificial neural networks provide a powerful tool to help doctors analyse, model and make sense of complex clinical data across a broad range of medical applications. Their potential in clinical medicine is reflected in the diversity of topics covered in this volume. In addition to looking at applications the book looks forward to exciting future prospects. A section on theory looks at approaches to validate and refine the results generated by artificial neural networks. The volume also recognizes that concerns exist about the use of 'black-box' systems as decision aids in medicine, and the final chapter considers the ethical and legal conundrums arising out of their use for diagnostic or treatment decisions. Taken together, this eclectic collection of chapters provides an exciting overview of harnessing the power of artificial neural networks in the investigation and treatment of disease.
Note:
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
,
1. Introduction / Richard Dybowski and Vanya Gant -- Part I. Applications -- 2. Artifical neural networks in laboratory medicine / Simon S. Cross -- 3. Using artifical neural networks to screen cervical smears: how new technology enhances health care / Mathilde E. Boon and Lambrecht P. Kok -- 4. Neural network analysis of sleep disorders / Lionel Tarassenko, Mayela Zamora and James Pardey -- 5. Artificial neural networks for neonatal intensive care / Emma A. Braithwaite [and others] -- 6. Artificial neural networks in urology: applications, feature extraction and user implementations / Craig S. Niederberger and Richard M. Golden -- 7. Artificial neural lnetworks as a tool for whole organism fingerprinting in bacterial taxonomy / Royston Goodacre -- Part I. Prospects -- 8. Recent advances in EEG signal analysis and classification / Charles W. Anderson and David A. Peterson.
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9. Adaptive resonance theory: a foundation for 'apprentice' systems in clinical decison support? / Robert F. Harrison [and others] -- 10. Evolving artificial neural networks / V. William Porto and David B. Fogel -- Part III. Theory -- 11. Neural networks as statistical methods in survival analysis / Brian D. Ripley and Ruth M. Ripley -- 12. A review of techniques for extracting rules from trained artificial neural networks / Robert Andrews, Alan B. Tickle and Joachim Diederich -- 13. Confidence intervals and prediction intervals for feedforward neural networks / Richard Dybowski and Stephen J. Roberts -- Part IV. Ethics and clinical prospects -- 14. Artificial neural networks: practical considerations for clinical application / Vanya Gant, Susan Rodway and Jeremy Wyatt.
Additional Edition:
Print version: ISBN 9780521662710
Language:
English
URL:
https://doi.org/10.1017/CBO9780511543494
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