| 2007 |
|---|
| 21 | EE | Jürgen Paetz:
Subrule Analysis and the Frequency-Confidence Diagram.
IDA 2007: 219-228 |
| 2006 |
|---|
| 20 | EE | Jürgen Paetz:
Evolution of Real Valued Weights for RBF-DDA Networks.
IJCNN 2006: 2907-2913 |
| 19 | EE | Jürgen Paetz:
Supervised Neuro-fuzzy Clustering for Life Science Applications.
ISBMDA 2006: 378-389 |
| 18 | EE | Jürgen Paetz:
Generalization Rules for Binarized Descriptors.
ISBMDA 2006: 72-82 |
| 17 | EE | Jürgen Paetz:
Optimization study with ligand-design interval rules.
Journal of Intelligent and Fuzzy Systems 17(3): 263-285 (2006) |
| 2005 |
|---|
| 16 | EE | Jürgen Paetz:
Comparing evolutionary optimization with ant colony optimization of drug design interval rules with and without pre-initialization.
Congress on Evolutionary Computation 2005: 267-273 |
| 15 | EE | Jürgen Paetz,
Gisbert Schneider:
A neuro-fuzzy approach to virtual screening in molecular bioinformatics.
Fuzzy Sets and Systems 152(1): 67-82 (2005) |
| 2004 |
|---|
| 14 | EE | Jürgen Paetz:
Evolving Scientific Knowledge.
Fuzzy Days 2004: 733-738 |
| 13 | EE | Jürgen Paetz:
Finding optimal decision scores by evolutionary strategies.
Artificial Intelligence in Medicine 32(2): 85-95 (2004) |
| 12 | EE | Jürgen Paetz,
Björn Arlt,
Kerstin Erz,
Katharina Holzer,
Rüdiger W. Brause,
Ernst Hanisch:
Data quality aspects of a database for abdominal septic shock patients.
Computer Methods and Programs in Biomedicine 75(1): 23-30 (2004) |
| 11 | EE | Jürgen Paetz:
Reducing the number of neurons in radial basis function networks with dynamic decay adjustment.
Neurocomputing 62: 79-91 (2004) |
| 2003 |
|---|
| 10 | | Jürgen Paetz:
Evolving Score Neural Networks.
IICAI 2003: 57-65 |
| 9 | | Jürgen Paetz:
Monte-Carlo Clustering by Neuro-Fuzzy Classification.
IICAI 2003: 66-72 |
| 8 | EE | Jürgen Paetz:
Knowledge-based approach to septic shock patient data using a neural network with trapezoidal activation functions.
Artificial Intelligence in Medicine 28(2): 207-230 (2003) |
| 2002 |
|---|
| 7 | | Jürgen Paetz:
Selecting the Representative Neuro-Fuzzy Model.
FSKD 2002: 737- |
| 6 | EE | Jürgen Paetz:
Intersection Based Generalization Rules for the Analysis of Symbolic Septic Shock Patient Data.
ICDM 2002: 673-676 |
| 5 | EE | Jürgen Paetz,
Björn Arlt:
A Neuro-fuzzy Based Alarm System for Septic Shock Patients with a Comparison to Medical Scores.
ISMDA 2002: 42-52 |
| 4 | EE | Jürgen Paetz,
Rüdiger W. Brause:
Rule generation and model selection used for medical diagnosis.
Journal of Intelligent and Fuzzy Systems 12(1): 69-78 (2002) |
| 2001 |
|---|
| 3 | EE | Jürgen Paetz:
Metric Rule Generation with Septic Shock Patient Data.
ICDM 2001: 637-638 |
| 2 | EE | Jürgen Paetz,
Rüdiger W. Brause:
A Frequent Patterns Tree Approach for Rule Generation with Categorical Septic Shock Patient Data.
ISMDA 2001: 207-212 |
| 2000 |
|---|
| 1 | EE | Jürgen Paetz,
Fred Henrik Hamker,
Sven Thöne:
About the Analysis of Septic Shock Patient Data.
ISMDA 2000: 130-137 |
