Ebook: Artificial Neural Networks in Biomedicine

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.

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This volume provides a state-of-the-art survey of artificial neural network applications in biomedical diagnosis, laboratory data analysis and related practical areas. It looks at biomedical applications which involve customising neural network technology to resolve specific difficulties with data processing, and deals with applications relating to particular aspects of clinical practice and laboratory or medically-related analysis. Each chapter is self-contained with regard to the technology used, covering important technical points and implementation issues like the design of user interfaces and hardware/software platforms. Artificial Neural Networks in Biomedicine will be of interest to computer scientists and neural network practitioners who want to extend their knowledge of issues relevant to biomedical applications, developers of clinical computer systems, and medical researchers looking for new methods and computational tools.

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This volume provides a state-of-the-art survey of artificial neural network applications in biomedical diagnosis, laboratory data analysis and related practical areas. It looks at biomedical applications which involve customising neural network technology to resolve specific difficulties with data processing, and deals with applications relating to particular aspects of clinical practice and laboratory or medically-related analysis. Each chapter is self-contained with regard to the technology used, covering important technical points and implementation issues like the design of user interfaces and hardware/software platforms. Artificial Neural Networks in Biomedicine will be of interest to computer scientists and neural network practitioners who want to extend their knowledge of issues relevant to biomedical applications, developers of clinical computer systems, and medical researchers looking for new methods and computational tools.
Content:
Front Matter....Pages i-xiv
Introduction....Pages 1-7
Front Matter....Pages 9-10
The Bayesian Paradigm: Second Generation Neural Computing....Pages 11-23
The Role of the Artificial Neural Network in the Characterisation of Complex Systems and the Prediction of Disease....Pages 25-37
Genetic Evolution of Neural Network Architectures....Pages 39-48
Front Matter....Pages 49-50
The Application of PAPNET to Diagnostic Cytology....Pages 51-67
ProstAsure Index — A Serum-Based Neural Network-Derived Composite Index for Early Detection of Prostate Cancer....Pages 69-79
Neurometric Assessment of Adequacy of Intraoperative Anaesthetic....Pages 81-91
Classifying Spinal Measurements Using a Radial Basis Function Network....Pages 93-104
Georgia: An Overview....Pages 105-115
Patient Monitoring Using an Artificial Neural Network....Pages 117-128
Benchmark of Approaches to Sequential Diagnosis....Pages 129-140
Application Of Neural Networks in the Diagnosis of Pathological Speech....Pages 141-150
Front Matter....Pages 151-152
Independent Components Analysis....Pages 153-168
Rest EEG Hidden Dynamics as a Discriminant for Brain Tumour Classification....Pages 169-180
Artificial Neural Network Control on Functional Electrical Stimulation Assisted Gait for Persons with Spinal Cord Injury....Pages 181-193
The Application of Neural Networks to Interpret Evoked Potential Waveforms....Pages 195-210
Front Matter....Pages 211-212
Intelligent Decision Support Systems in the Cytodiagnosis of Breast Carcinoma....Pages 213-231
A Neural-Based System for the Automatic Classification and Follow-Up of Diabetic Retinopathies....Pages 233-247
Classification of Chromosomes: A Comparative Study of Neural Network and Statistical Approaches....Pages 249-265
The Importance of Features and Primitives for Multi-dimensional/Multi-channel Image Processing....Pages 267-282
Back Matter....Pages 283-287

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This volume provides a state-of-the-art survey of artificial neural network applications in biomedical diagnosis, laboratory data analysis and related practical areas. It looks at biomedical applications which involve customising neural network technology to resolve specific difficulties with data processing, and deals with applications relating to particular aspects of clinical practice and laboratory or medically-related analysis. Each chapter is self-contained with regard to the technology used, covering important technical points and implementation issues like the design of user interfaces and hardware/software platforms. Artificial Neural Networks in Biomedicine will be of interest to computer scientists and neural network practitioners who want to extend their knowledge of issues relevant to biomedical applications, developers of clinical computer systems, and medical researchers looking for new methods and computational tools.
Content:
Front Matter....Pages i-xiv
Introduction....Pages 1-7
Front Matter....Pages 9-10
The Bayesian Paradigm: Second Generation Neural Computing....Pages 11-23
The Role of the Artificial Neural Network in the Characterisation of Complex Systems and the Prediction of Disease....Pages 25-37
Genetic Evolution of Neural Network Architectures....Pages 39-48
Front Matter....Pages 49-50
The Application of PAPNET to Diagnostic Cytology....Pages 51-67
ProstAsure Index — A Serum-Based Neural Network-Derived Composite Index for Early Detection of Prostate Cancer....Pages 69-79
Neurometric Assessment of Adequacy of Intraoperative Anaesthetic....Pages 81-91
Classifying Spinal Measurements Using a Radial Basis Function Network....Pages 93-104
Georgia: An Overview....Pages 105-115
Patient Monitoring Using an Artificial Neural Network....Pages 117-128
Benchmark of Approaches to Sequential Diagnosis....Pages 129-140
Application Of Neural Networks in the Diagnosis of Pathological Speech....Pages 141-150
Front Matter....Pages 151-152
Independent Components Analysis....Pages 153-168
Rest EEG Hidden Dynamics as a Discriminant for Brain Tumour Classification....Pages 169-180
Artificial Neural Network Control on Functional Electrical Stimulation Assisted Gait for Persons with Spinal Cord Injury....Pages 181-193
The Application of Neural Networks to Interpret Evoked Potential Waveforms....Pages 195-210
Front Matter....Pages 211-212
Intelligent Decision Support Systems in the Cytodiagnosis of Breast Carcinoma....Pages 213-231
A Neural-Based System for the Automatic Classification and Follow-Up of Diabetic Retinopathies....Pages 233-247
Classification of Chromosomes: A Comparative Study of Neural Network and Statistical Approaches....Pages 249-265
The Importance of Features and Primitives for Multi-dimensional/Multi-channel Image Processing....Pages 267-282
Back Matter....Pages 283-287
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