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ORCIDArtificial Intelligence in Medicine, Volume 28
Volume 28, Number 1, May 2003
- Paulo J. G. Lisboa, H. Wong, P. Harris, R. Swindell:
A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer. 1-25 - Dragan Gamberger, Nada Lavrac:
Active subgroup mining: a case study in coronary heart disease risk group detection. 27-57 - Carsten Peterson, Markus Ringnér
:
Analyzing tumor gene expression profiles. 59-74 - Andreas Alexander Albrecht, Staal Amund Vinterbo, Lucila Ohno-Machado:
An Epicurean learning approach to gene-expression data classification. 75-87 - Christopher J. James, David Lowe:
Extracting multisource brain activity from a single electromagnetic channel. 89-104 - Ralf Schweiger, Simon Hölzer, Dirk Rudolf, Joerg Rieger, Joachim Dudeck:
Linking clinical data using XML topic maps. 105-115
Volume 28, Number 2, June 2003
- Ian Cloete, Karl Rohr:
Knowledge-based neurocomputing in medicine. 117-119 - Christian W. Omlin, Sean Snyders:
Inductive bias strength in knowledge-based neural networks: application to magnetic resonance spectroscopy of breast tissues. 121-140 - Guido Bologna:
A model for single and multiple knowledge based networks. 141-163 - Matthias E. Futschik, Anthony Reeve, Nikola K. Kasabov:
Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue. 165-189 - Robert Wall, Padraig Cunningham, Paul Walsh, Stephen Byrne:
Explaining the output of ensembles in medical decision support on a case by case basis. 191-206 - Jürgen Paetz:
Knowledge-based approach to septic shock patient data using a neural network with trapezoidal activation functions. 207-230
Volume 28, Number 3, July 2003
- Guy Carrault, Marie-Odile Cordier, Rene Quiniou, Feng Wang:
Temporal abstraction and inductive logic programming for arrhythmia recognition from electrocardiograms. 231-263 - Frank Dieterle, Silvia Müller-Hagedorn, Hartmut M. Liebich, Günter Gauglitz:
Urinary nucleosides as potential tumor markers evaluated by learning vector quantization. 265-279 - Chuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Ignace Vergote, Dirk Timmerman:
Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines. 281-306 - Sergio Di Bona, Heinrich Niemann, Gabriele Pieri, Ovidio Salvetti:
Brain volumes characterisation using hierarchical neural networks. 307-322 - Martin Radespiel-Tröger, Thomas Rabenstein, H. T. Schneider, Berthold Lausen:
Comparison of tree-based methods for prognostic stratification of survival data. 323-341
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