Artificial Neural Networks in Medicine and Biology: Proceedings of the Annimab-1 Conference, Gateborg, Sweden, 13-16 May 2000 Book

Invited Presentations:
Neural Computation in Medicine: Perspectives and Prospects; An Unsupervised Learning Method that Produces Organized Representations from Real Information; On Forgetful Attractor Network Memories; ART Neural Networks for Medical Data Analysis and Fast Distributed Learning; Discriminating Gourmets, Lovers and Enophiles? Neural Nets Tell All About Locusts, Toads and Roaches; Protein Beta-Sheet Partner Prediction by Neural Networks.- Medical Image Analysis: Cancerous Liver Tissue Differentiation Using LVQ; Quantification of Diabetic Retinopathy Using Neural Networks and Sensitivity Analysis; Internet Based Artificial Neural Networks for the Interpretation of Medical Images; Segmentation of Magnetic Resonance Images According to Contrast Agent Uptake Kinetics Using a Competitive Neural Network; Applications of Optimizing Neural Networks in Medical Image Registration; Detection of Features from Medical Images Using a Modular Network Approach that Relies on Learning by Sample; Neural Network Based Classification of Cell Images via Estimation of Fractal Dimensions.- Signal Processing in Medicine: Mutual Control Neural Networks for Sleep Arousal Detection; Extraction of Sleep-Spindles from the Electroencephalogram (EEG); Analyzing Brain Tumor Related EEG Signals with ICA Algorithms; Isolating Seizure Activity in the EEG with Independent Component Analysis; Seizure Detection with the Self-Organising Feature Map; Neural Network Approach to P Wave Detection in the Electrocardiogram; Graphical Analysis of Respiration in Postoperative Patients Using Self-Organising Maps.- Clinical Diagnosis and Medical Decision Support: Neural Network Predictions of Outcome from Posteroventral Pallidotomy; A Neural-Bayesian Approach to Survival Analysis; Identifying Discriminant Features in the Histopathology Diagnosis of Inflammatory Bowel Disease Using a Novel Variant of the Growing Cell Structure Network Technique; Classifying Pigmented Skin Lesions with Machine Learning Methods; An Assessment System of Dementia of Alzheimer Type Using Artificial Neural Networks; A New Artificial Neural Network Method for the Interpretation of ECGs; Use of a Kohonen Neural Network to Characterize Respiratory Patients for Medical Intervention; determination of Microalbuminuria and Increased Urine Albumin Excretion by Immunoturbidimetric Assay and Neural Networks; Using an Artificial neural network to Predict Postoperative nausea and Vomiting; Acute Myocardial Infarction: Analysis of the ECH Using Artificial Neural Networks; Bayesian Neural Networks Used to Find Adverse Drug Combinations and Drug Related Syndromes; Monitoring of Physiological Parameters of Patients and Therapists During Psychotherapy Sessions Using Self-Organizing Maps.- Biomolecular Applications and Biological Modelling: Neuronal Network Modelling of the Somatosensory Pathway and its Application to General Anaesthesia; Electronic Noses and their Applications; A Hybrid Classification Tree and Artificial Neural Network Model for Predicting the In Vitro Response of the Human Immunodeficiency Virus (HIV1) to Anti-Viral Drug Therapy; Neural Unit Sensitive to Modulation; On Methods for Combination of Results from Gene-Finding Programs for Improved Prediction Accuracy; A Simulation Model for Activated Sludge Process Using Fuzzy Neural Networks; A General Method for Combining Predictors Tested on Protein Secondary Structure Prediction; A Three-Neuron Model of Information Processing During Bayesian Foraging; Sensorimotor Sequential Learning by an Artificial Neural Network based on Re-Defined Hebbian Learning; On Synaptic Plasticity: Modelling Molecular Kinases Involved in Transmitter Release; Self-Organizing Networks for Mapping and Clustering Biological Macromolecule Images; A Neural Network Model for Muscle Force Control Based on the Size Principle and Recurrent Inhibition of Renshaw Cells; Prediction of Photosensitizer Activity in Photodynamic Therapy Using Artificial Neural Networks: A 3D-QSAR Study.- Learning Methods and Hybrid Algorithms: Providing Case-Based Explanations for Artificial Neural Nets; Double Growing Neural Gas for Disease Diagnosis; The Use of a Knowledge Discovery Method for the Development of a Multi-Layer Perceptron Network that Classifies Low Back Pain Patients; Kernel PCA Feature Extraction of Event -Related Potentials for Human Signal Detection Performance; Particle Swarm Optimisation in Feedforward Neural Networks.