Table of contents of journal:

Results: 14

Clinical applications of artificial neural networks - Introduction

Authors: Dybowski, R Gant, V

Citation: R. Dybowski et V. Gant, Clinical applications of artificial neural networks - Introduction, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 1-27

Artificial neural networks in laboratory medicine

Authors: Cross, SS

Citation: Ss. Cross, Artificial neural networks in laboratory medicine, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 31-80

Using artificial neural networks to screen cervical smears: how new technology enhances health care

Authors: Boon, ME Kok, LP

Citation: Me. Boon et Lp. Kok, Using artificial neural networks to screen cervical smears: how new technology enhances health care, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 81-89

Neural network analysis of sleep disorders

Authors: Tarassenko, L Zamora, M Pardey, J

Citation: L. Tarassenko et al., Neural network analysis of sleep disorders, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 90-101

Artificial neural networks for neonatal intensive care

Authors: Braithwaite, EA Dripps, J Lyon, AJ Murray, A

Citation: Ea. Braithwaite et al., Artificial neural networks for neonatal intensive care, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 102-119

Artificial neural networks in urology: applications, feature extraction and user implementations

Authors: Niederberger, CS Golden, RM

Citation: Cs. Niederberger et Rm. Golden, Artificial neural networks in urology: applications, feature extraction and user implementations, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 120-142

Artificial neural networks as a tool for whole organism fingerprinting in bacterial taxonomy

Authors: Goodacre, R

Citation: R. Goodacre, Artificial neural networks as a tool for whole organism fingerprinting in bacterial taxonomy, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 143-171

Recent advances in EEG signal analysis and classification

Authors: Anderson, CW Peterson, DA

Citation: Cw. Anderson et Da. Peterson, Recent advances in EEG signal analysis and classification, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 175-191

Adaptive resonance theory: a foundation for 'apprentice' systems in clinical decision support?

Authors: Harrison, RF Cross, SS Kennedy, RL Lim, CP Downs, J

Citation: Rf. Harrison et al., Adaptive resonance theory: a foundation for 'apprentice' systems in clinical decision support?, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 192-222

Evolving artificial neural networks

Authors: Porto, VW Fogel, DB

Citation: Vw. Porto et Db. Fogel, Evolving artificial neural networks, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 223-234

Neural networks as statistical methods in survival analysis

Authors: Ripley, BD Ripley, RM

Citation: Bd. Ripley et Rm. Ripley, Neural networks as statistical methods in survival analysis, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 237-255

A review of techniques for extracting rules from trained artificial neuralnetworks

Authors: Andrews, R Tickle, AB Diederich, J

Citation: R. Andrews et al., A review of techniques for extracting rules from trained artificial neuralnetworks, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 256-297

Confidence intervals and prediction intervals for feedforward neural networks

Authors: Dybowski, R Roberts, SJ

Citation: R. Dybowski et Sj. Roberts, Confidence intervals and prediction intervals for feedforward neural networks, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 298-326

Artificial neural networks: practical considerations for clinical application

Authors: Gant, V Rodway, S Wyatt, J

Citation: V. Gant et al., Artificial neural networks: practical considerations for clinical application, CLINICAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS, 2001, pp. 329-356

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