Lisboa / Ifeachor / Szczepaniak Artificial Neural Networks in Biomedicine

Erscheinungsjahr 2012
ISBN: 978-1-4471-0487-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 288 Seiten, eBook

Reihe: Perspectives in Neural Computing

Following the intense research activIties of the last decade, artificial neural networks have emerged as one of the most promising new technologies for improving the quality of healthcare. Many successful applications of neural networks to biomedical problems have been reported which demonstrate, convincingly, the distinct benefits of neural networks, although many ofthese have only undergone a limited clinical evaluation. Healthcare providers and developers alike have discovered that medicine and healthcare are fertile areas for neural networks: the problems here require expertise and often involve non-trivial pattern recognition tasks - there are genuine difficulties with conventional methods, and data can be plentiful. The intense research activities in medical neural networks, and allied areas of artificial intelligence, have led to a substantial body of knowledge and the introduction of some neural systems into clinical practice. An aim of this book is to provide a coherent framework for some of the most experienced users and developers of medical neural networks in the world to share their knowledge and expertise with readers.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Lisboa, Paulo J.G.

Ifeachor, Emmanuel C.

Szczepaniak, Piotr S.

Inhaltsverzeichnis

Tutorial and Review.- 1 The Bayesian Paradigm: Second Generation Neural Computing.- 2 The Role of the Artificial Neural Network in the Characterisation of Complex Systems and the Prediction of Disease.- 3 Genetic Evolution of Neural Network Architectures.- Computer Aided Diagnosis.- 4 The Application of PAPNET to Diagnostic Cytology.- 5 ProstAsure Index — A Serum-Based Neural Network-Derived Composite Index for Early Detection of Prostate Cancer.- 6 Neurometric Assessment of Adequacy of Intraoperative Anaesthetic.- 7 Classifying Spinal Measurements Using a Radial Basis Function Network.- 8 GEORGIA: An Overview.- 9 Patient Monitoring Using an Artificial Neural Network.- 10 Benchmark of Approaches to Sequential Diagnosis.- 11 Application of Neural Networks in the Diagnosis of Pathological Speech.- Signal Processing.- 12 Independent Components Analysis.- 13 Rest EEG Hidden Dynamics as a Discriminant for Brain Tumour Classification.- 14 Artifical Neural Network Control on Functional Electrical Stimulation Assisted Gait for Persons with Spinal Cord Injury.- 15 The Application of Neural Networks to Interpret Evoked Potential Waveforms.- Image Processing.- 16 Intelligent Decision Support Systems in the Cytodiagnosis of Breast Carcinoma.- 17 A Neural-Based System for the Automatic Classificaton and Follow-Up of Diabetic Retinopathies.- 18 Classification of Chromosomes: A Comparative Study of Neural Network and Statistical Approaches.- 19 The Importance of Features and Primitives for Multi-dimensional/Multi-channel Image Processing.