Publications

Original Articles

1

H. A. Kestler, A. A. Farschtschi, and P. H. Wein.
Untersuchung und Simulation Neuronaler Netze mit dynamischer Strukturänderung.
Automatisierungstechnische Praxis, 36(2):47-51, 1994.

2

H. A. Kestler, S. Janko, U. Häußler, R. Muche, M. Höher, V. Hombach, and J. Wiecha.
A remark on the high- conductance calcium activated potassium channel in human endothelial cells.
Res Exp Med, 198(3):133-143, 1998.

3

M. Haschka and H. A. Kestler.
Squinting and stereoscopic vision.
Phys. Educ., 34(5):316-320, 1999.

4

T. Mattfeldt, H. A. Kestler, R. Hautmann, and H.-W. Gottfried.
Prediction of prostatic cancer progrssion after radical prostatectomy using artificial neural networks: a feasibility study.
BJU International, 84:316-323, 1999.

5

H. A. Kestler, M. Schulé, F. Schwenker, H. Neumann, and T. Mattfeldt.
Neural Classification of Cytological Smears from the Cervix.
Biomed. Technik, 44:17-24, 1999.
in german.

6

H. A. Kestler and M. Haschka.
A Model for the Emergence of Café-au-Lait Macules.
The Journal of Investigative Dermatology, 113:858-859, 1999.

7

H. A. Kestler, J. Wöhrle, and M. Höher.
Cardiac vulnerability assessment from electrical microvariability of the high-resolution electrocardiogram.
Medical & Biological Engineering & Computing, 38:88-92, 2000.

8

H. A. Kestler, S. Sablatnög, S. Simon, S. Enderle, A. Baune, G. K. Kraetzschmer, F. Schwenker, and G. Palm.
Concurrent Object Indentification and Localization for a Mobile Robot.
Künstliche Intelligenz, (4):23-29, 2000.

9

M. Haschka and H. A. Kestler.
Warum sind Pfützen elliptisch.
Der mathematische und naturwissenschaftliche Unterricht, 53(4):209-212, 2000.

10

T. Mattfeldt, H.-W. Gottfried, V. Schmidt, and H. A. Kestler.
Classification of spatial textures in benign and cancerous glandular tissues by stereology and stochastic geometry using artificial neural networks.
Journal of Microscopy, 198:143-158, 2000.

11

H. A. Kestler.
ROC with confidence - a Perl program for receiver operator characteristic curves.
Computer Methods and Programs in Biomedicine, 64(2):133-136, 2001.

12

F. Schwenker, H. A. Kestler, and G. Palm.
Three learning phases for radial-basis-function networks.
Neural Networks, 14(4-5):439-458, 2001.

13

T. Mattfeldt, H. A. Kestler, R. Hautmann, and H.-W. Gottfried.
Prediction of Postoperative Prostatic Cancer Stage on the Basis of Systematic Biopsies using Two Types of Artificial Neural Networks.
European Urology, 39:530-537, 2001.

14

O. Grebe, M. Giesler, H. A. Kestler, V. Hombach, and M. Höher.
Magnetic Resonance Imaging After Percutaneous Closure of a Patent Foramen Ovale.
Circulation, 104(22):e117-e118, 2001.

15

T. Mattfeldt, H. Wolter, R. Kemmerling, H.-W. Gottfried, and H. A. Kestler.
Cluster analysis of comparative genomic hybridization (CGH) data using self-organizing maps: Application to prostate carcinomas.
Analytical Cellular Pathology, 23(1):29-37, 2001.

16

T. Mattfeldt, H. Wolter, D. Trijic, H.-W. Gottfried, and H. A. Kestler.
Chromosomal regions in prostatic carcinomas studied by comparative genomic hybridization, hierarchical cluster analysis and self-organizing feature maps.
Analytical Cellular Pathology, 24:167-179, 2002.

17

F. Schwenker, C. Dietrich, H. A. Kestler, K. Riede, and G. Palm.
Radial Basis Function Neural Networks and Temporal Fusion for the Classification of Bioacoustic Time Series.
Neurocomputing, 51:265-275, 2003.

18

J. Wöhrle, T. Nusser, A. Hoffmeister, H. A. Kestler, O. C. Grebe, M. Höher, W. Koenig, V. Hombach, and M. Kochs.
Einfluß von Molisdomin auf rheologische Parameter und das Auftreten kardiovaskulärer Ereignisse bei Patienten mit koronarer Herzkrankheit.
Deutsche Medizinische Wochenschrift, 128:1333-1337, 2003.

19

O. Grebe, I. Paetsch, H. A. Kestler, B. Herkommer, B. Schnackenburg, V. Hombach, E. Fleck, and E. Nagel.
Optimal acquisition parameters for contrast enhanced magnetic resonance imaging after chronic myocardial infarction.
J Cardiovasc Magn Reson, 5:575-587, 2003.

20

T. Mattfeldt, H.-W. Gottfried, H. Wolter, V. Schmidt, H. A. Kestler, and J. Mayer.
Classification of Prostatic Carcinoma with Artificial Neural Networks Using Comparative Genomic Hybridization and Quantitative Stereological Data.
Pathology Res Pract, 199:773-784, 2003.

21

H. Fensterer, K. Giehl, M. Buchholz, V. Ellenrieder, A. Buck, H. A. Kestler, G. Adler, P. Gierschick, and T.M. Gress.
Expression Profiling of the Influence of RAS Mutants on the TGFB1-Induced Phenotype of the Pancreatic Cancer Cell Line PANC-1.
Genes, Chromosomes and Cancer, 39:224-235, 2004.

22

T. Mattfeldt, D. Trijic, H.-W. Gottfried, and H. A. Kestler.
Incidental carcinoma of the prostate: clinicopathological, stereological and immunohistochemical findings studied with logistic regression and self-organizing feature maps.
BJU International, 93:284-290, 2004.

23

J. Wöhrle, M. Kochs, C. Vollmer, H. A. Kestler, V. Hombach, and M. Höher.
Re-angioplasty of in-stent restenosis versus balloon restenoses-a matched pair comparison.
Int J Cardiol, 93:257-62, 2004.

24

C. Schwaenen, M Nessling, S. Wessendorf, T. Salvi, G. Wrobel, B. Radlwimmer, H. A. Kestler, C. Haslinger, S. Stilgenbauer, H. Döhner, M. Bentz, and P. Lichter.
Automated array-based genomic profiling in chronic lymphocytic leukemia: Development of a clinical tool and discovery of recurrent genomic alterations.
PNAS, 101:1039-1044, 2004.

25

H. Kohlhammer, C. Schwaenen, S. Wessendorf, K. Holzmann, H. A. Kestler, D. Kienle, T. F. Barth, P. Möller, G. Ott, J. Kalla, B. Radlwimmer, A. Pscherer, S. Stilgenbauer, H. Döhner, P. Lichter, and M. Bentz.
Genomic DNA-chip hybridization in t(11;14)-positive mantle cell lymphomas shows a high frequency of aberrations and allows a refined characterization of consensus regions.
Blood, 104(3):795-801, 2004.

26

K. Holzmann, H. Kohlhammer, C. Schwaenen, S. Wessendorf, H. A. Kestler, A. Schwoerer, B. Rau, B. Radlwimmer, H. Döhner, P. Lichter, T. Gress, and M. Bentz.
Genomic DNA-chip hybridization reveals a higher incidence of genomic amplifications in pancreatic cancer than conventional comparative genomic hybridization and leads to the identification of novel candidate genes.
Cancer Research, 46(13):4428-33, 2004.

27

T. Mattfeldt, H. A. Kestler, and H.-P. Sinn.
Prediction of the axillary lymph node status in mammary cancer on the basis of clinicopathological data and flow cytometry.
Medical & Biological Engineering & Computing, 42:733-739, 2004.

28

V. Hombach, O. Grebe, N. Merkle, S. Waldenmaier, M. Hoher, M. Kochs, J. Wohrle, and H. A. Kestler.
Sequelae of acute myocardial infarction regarding cardiac structure and function and their prognostic significance as assessed by magnetic resonance imaging.
Eur Heart J, 26(6):549-557, 2005.

29

M. Buchholz, H. A. Kestler, K. Holzmann, V. Ellenrieder, W. Schneiderhan, M. Siech, G. Adler, M. G. Bachem, and T. M. Gress.
Transcriptome analysis of human hepatic and pancreatic staellate cells: organ-specific variations of a common transcriptional phenotype.
J Molecular Medicine, 83(10):795-805, 2005.
MB and HAK contributed equally.

30

S. Kempe, H. A. Kestler, A. Lasar, and T. Wirth.
NF-kappaB controls the global pro-inflammatory response in endothelial cells: evidence for the regulation of a pro-atherogenic program.
Nucleic Acids Res, 33(16):5308-19, 2005.

31

M. Buchholz, M. Braun, A. Heidenblut, H. A. Kestler, G. Klöppel, W. Schmiegel, S. A. Hahn, J. Lüttges, and T. M. Gress.
Transcriptome analysis of microdissected pancreatic intraepithelial neoplasitc lesions.
Oncogene, 24(44):6626-36, 2005.

32

M. Buchholz, H. A. Kestler, A. Bauer, W. Böck, B. Rau, G. Leder, W. Kratzer, M. Bommer, A. Scarpa, M. K. Schilling, G. Adler, J. D. Hoheisel, and T. M. Gress.
Specialized DNA arrays for the differentiation of pancreatic tumors.
Clin Cancer Res, 11(22):8048-54, 2005.
HAK and MB contributed equally.

33

H. A. Kestler, A. Müller, T. M. Gress, and M. Buchholz.
Generalized Venn Diagrams: A new method of visualizing complex genetic set relations.
Bioinformatics, 21(6):733-739, 2005.

Overview Articles

34

H. A. Kestler, V. Hombach, H.-H. Osterhues, M. Kochs, and M. Höher.
Non-invasive Risk Stratification in Patients after Myocardial Infarction - A Brief Review.
Biocybernetics and Biomedical Engineering, 20(1):67-79, 2000.

35

C. Schwaenen, S. Wessendorf, H. A. Kestler, H. Döhner, P. Lichter, and M. Bentz.
DNA microarray analysis in malignant lymphomas.
Ann Hematol, 83:323-332, 2003.

36

H. A. Kestler and R. Küfer.
Wertigkeit und Notwendigkeit bioinformatischer Methoden zur Mikroarray-Datenanalyse.
Urologe A, 43:669-674, 2004.

Conference Papers

37

F. Schwenker, H. A. Kestler, and G. Palm.
A Comparison of LVQ and RBF Networks for Classification and Data Clustering.
In Proceedings of the 6th Microcomputer School, pages 646-651, Brno, 1994.

38

F. Schwenker, H. A. Kestler, G. Palm, and M. Höher.
Similarities of LVQ and RBF Learning - A survey of learning rules and the application to the the classification of signals from high-resolution electrocardiography.
In Proceedings of the International Conference on Systems, Man, and Cybernetics, pages 646-651. IEEE, 1994.

39

M. Höher, H. A. Kestler, S. Bauer, P. Weismüller, G. Palm, and V. Hombach.
Neural Network Based Analysis of the Signal Averaged Electrocardiogram.
In A. Murray and R. Arzbaecher, editors, IEEE Computers in Cardiology, pages 257-260. IEEE Computer Society, 1995.

40

H. A. Kestler, F. Schwenker, and M. Höher.
Combining Supervised Competitive Learning and Gradient Descent Learning to Classify Signal-Averaged High-Resolution Electrograms.
In A. Murray and R. Arzbaecher, editors, IEEE Computers in Cardiology, pages 381-384. IEEE Computer Society, 1995.

41

H. A. Kestler, F. Schwenker, M. Hoeher, and G. Palm.
Adaptive Class-Specific Partitioning as a Means of Initializing RBF-Networks.
In Proceedings of the International Conference on Systems, Man, and Cybernetics, pages 46-49. IEEE, 1995.

42

F. Schwenker, H. A. Kestler, M. Höher, and G. Palm.
Klassifikation hochverstärkter EKG Signale durch RBF Netzwerke.
In G. Sagerer, S. Posch, and F. Kummert, editors, Mustererkennung 1995, pages 387-394. Springer Verlag, 1995.

43

H. A. Kestler, M. Höher, G. Palm, M. Kochs, and V. Hombach.
Time Domain Variability of High Resolution Beat-to-Beat Recordings Classified by Neural Networks.
In A. Murray and R. Arzbaecher, editors, IEEE Computers in Cardiology, pages 317-320. IEEE Computer Society, 1996.

44

H. A. Kestler, M. Höher, F. Schwenker, and V. Hombach.
Filtering Beat-to-Beat Recordings of the High Resolution Electrocardiogram.
In A. Murray and R. Arzbaecher, editors, IEEE Computers in Cardiology, pages 461-464. IEEE Computer Society, 1996.

45

F. Schwenker, H. A. Kestler, and G. Palm.
Visualization and Analysis of Signal Averaged High Resolution Electrocardiograms Employing Cluster Analysis and Multidimensional Scaling.
In A. Murray and R. Arzbaecher, editors, IEEE Computers in Cardiology, pages 453-456. IEEE Computer Society, 1996.

46

M. Höher, D. E. Ritscher, S. Bauer, M. Kodler, H. A. Kestler, and V. Hombach.
Beat-to-Beat Variability of QRS Duration: Initial Results from a Large ECG Database with Prospective Follow-up.
In A. Murray and S. Swiryn, editors, IEEE Computers in Cardiology, pages 613-616. IEEE Computer Society, 1997.

47

H. A. Kestler, F. Schwenker, G. Palm, V. Hombach, and M. Höher.
Neuronale Netze zur Visualisierung und Klassifikation - Anwendung auf hochverstärkte EKG Signale.
In R. Muche, G. Büchele, D. Harder, and W. Gaus, editors, Medizinische Informatik, Biometrie und Epidemiologie - GMDS 97, pages 90-95, München, 1997. MMV Medizin Verlag.

48

H. A. Kestler, H. Strey, H. Dickhaus, G. Palm, V. Hombach, and M. Höher.
Diskrete Waveletanalyse des signalgemittelten, hochauflösenden Elektrokardiogramms.
In R. Muche, G. Büchele, D. Harder, and W. Gaus, editors, Medizinische Informatik, Biometrie und Epidemiologie - GMDS 97, pages 96-101, München, 1997. MMV Medizin Verlag.

49

H. A. Kestler, H. Strey, H. Dickhaus, G. Palm, V. Hombach, and M. Höher.
Discrete Wavelet Analysis of the Signal-Averaged High-Resolution Electrocardiogram.
In A. Murray and S. Swiryn, editors, IEEE Computers in Cardiology, pages 621-624. IEEE Computer Society, 1997.

50

H. A. Kestler, M. Haschka, W. Kratz, F. Schwenker, G. Palm, V. Hombach, and M. Höher.
De-noising of High- resolution ECG Signals by Combining the Discrete Wavelet Transform with the Wiener Filter.
In A. Murray and S. Swiryn, editors, IEEE Computers in Cardiology, pages 233-236. IEEE Computer Society, 1998.

51

A. Wichert and H. A. Kestler.
A categorical based reanimation expert system.
In E.C. Ifeachor, A. Sperduti, and A. Starita, editors, Neural Networks and Expert Systems in Medicine and Healthcare, pages 187-193. World Scientific, 1998.

52

A. Baune, S. Simon, H. A. Kestler, F. Schwenker, and G. Palm.
Schritthaltende Objektklassifikation für einen autonomen mobilen Roboter.
In G. Schmidt, U. Hanebeck, and F. Freyberger, editors, Autonome Mobile Systeme 1999, pages 254-261. Springer Verlag, Berlin, 1999.

53

M. Höher, T. Brummer, and H. A. Kestler.
Concept and Initial Experience with a Mid-term DICOM Archiving System Acting as an Intelligent Buffer to Clinical Requests.
IEEE Computers in Cardiology, 26:319-322, 1999.

54

S. Simon, H. A. Kestler, A. Baune, F. Schwenker, and G. Palm.
Object classification with simple visual attention and a hierarchical neural network for subsymbolic-symbolic coupling.
In Proceedings of the 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA'99, pages 244-249. IEEE, 1999.

55

H. A. Kestler, S. Simon, A. Baune, F. Schwenker, and G. Palm.
Object Classification Using Simple, Colour Based Visual Attention and a Hierarchical Neural Network for Neuro-Symbolic Integration.
In W. Burgard, T. Christaller, and A. B. Cremers, editors, KI-99 Advances in Artificial Intelligence, pages 267-279. Springer Verlag, Berlin, 1999.

56

H. A. Kestler, S. Simon, A. Baune, M. Hagenbuchner, F. Schwenker, and G. Palm.
A Hierarchical Neural Object Classifier for Subsymbolic-Symbolic Coupling.
In W. Förster, J. M. Buhmann, A. Faber, and P. Faber, editors, Mustererkennung 1999, pages 27-35. Springer Verlag, Berlin, 1999.

57

H. A. Kestler, F. Schwenker, G. Hafner, V. Hombach, G. Palm, and M. Höher.
Feasibility Study of Complete Neural Net Based Classification of Signal-Averaged High-Resolution ECGs.
IEEE Computers in Cardiology, 26:575-578, 1999.

58

S. Simon, F. Vogt, H. A. Kestler, F. Schwenker, and G. Palm.
Aufmerksamkeitssteuerung für die Objektklassifikation auf einem autonomen mobilen Roboter.
In G. Baratoff and H. Neumann, editors, Dynamische Perzeption, pages 195-198, Berlin, 2000. Akademische Verlagsgesellschaft.

59

F. Schwenker, H. A. Kestler, and G. Palm.
An Algorithm for Adaptive Clustering and Visualization of Highdimensional Data Sets.
In G. Della Riccia, R. Kruse, and H. J. Lenz, editors, Computational Intelligence in Data Mining, pages 127-140. Springer, Wien, 2000.

60

F. Schwenker, H. A. Kestler, and G. Palm.
Combination of Supervised and Unsupervised Learning for Radial-Basis-Function Networks.
In H. H. Bothe and R. Rojas, editors, Second International ICSC Symposium on Neural Computation (NC'2000), pages 22-28. ICSC Academic Press, Wetaskiwin, Canada, 2000.

61

F. Schwenker, H. A. Kestler, and G. Palm.
Radial-Basis-Function Networks: Learning and Applications.
In R.J. Howlett and L.C. Jain, editors, Fourth International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies, pages 33-43. IEEE, Piscataway, 2000.

62

M. Höher, J. Wöhrle, B. Scharf, S. Thamasett, S. Stiller, S. Bauer, and H. A. Kestler.
Heart-Rate Dependency of QRS-Microvariability During Atrial Pacing.
IEEE Computers in Cardiology, 27:727-730, 2000.

63

H. A. Kestler, M. Haschka, A. Müller, F. Schwenker, G. Palm, and M. Höher.
Evolutionary Optimization of a Wavelet Classifier for the Categorization of Beat-to-Beat Variability Signals.
IEEE Computers in Cardiology, 27:715-718, 2000.

64

F. Schwenker and H. A. Kestler.
Decision Trees for the Analysis and Classification of Signal Averaged High-Resolution ECGs.
Biomed. Technik, 45(Suppl. 2):191-194, 2000.

65

H. A. Kestler and G. Palm.
A simple evolutionary wavelet classifier for the categorization of beat-to-beat variability signals.
Biomed. Technik, 45(Suppl. 2):30-35, 2000.

66

A. Wichert, H. A. Kestler, H. Walter, G. Grön, A. Baune, J. Grothe, A. Wunderlich, and F. T. Sommer.
Explorative detection of delay activity during a working memory task.
In G.M. Papadourakis, editor, Neural Networks and Expert Systems in Medicine and Healthcare, pages 266-271. Technological Educational Institute of Crete, 2001.

67

H. A. Kestler, M. Höher, and F. Schwenker.
Evolutionary Optimization of a Wavelet Classifier for the Categorization of Beat-to-Beat Variability Signals.
In V. Kurkova, N.C. Steele, R. Neruda, and M. Karny, editors, Artificial Neural Nets and Genetic Algorithms, pages 280-283. Springer-Verlag, Wien, 2001.

68

F. Schwenker, H. A. Kestler, S. Simon, and G. Palm.
3D Object Recognition for Autonomous Mobile Robots Utilizing Support Vector Classifiers.
In Proceedings of the 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2001, pages 344-349. IEEE, 2001.

69

H. A. Kestler, F. Schwenker, J. Wöhrle, V. Hombach, G. Palm, and M. Höher.
Combined Assessment of Beat-to-Beat Micro-Variability and Signal-Averaged ECG Parameters.
IEEE Computers in Cardiology, 28:73-76, 2001.

70

O. Grebe, M. Höher, F. Schwenker, H. Neumann, J. Wöhrle, G. Palm, V. Hombach, and H. A. Kestler.
New Markers for Diastolic Function by Cardiac Magnetic Resonance Imaging.
IEEE Computers in Cardiology, 28:625-628, 2001.

71

H. A. Kestler, A. Müller, V. Hombach, J. Wöhrle, G. Palm, M. Höher, and F. Schwenker.
Decision fusion of micro-variability and signal-averaged ECG parameters from the QRS complex with RBF networks.
IEEE Computers in Cardiology, 29:297-300, 2002.

72

F. Schwenker and H. A. Kestler.
Analysis of support vectors helps to identify borderline patients in classification studies.
IEEE Computers in Cardiology, 29:305-308, 2002.

73

O. Grebe, M. Lehn, H. Neumann, F. Schwenker, J. Wöhrle, M. Höher, V. Hombach, and H. A. Kestler.
Parameters for characterizing diastolic function with cardiac magnetic resonance imaging.
IEEE Computers in Cardiology, 29:185-188, 2002.

74

S. Simon, F. Schwenker, H. A. Kestler, G. Kraetzschmar, and G. Palm.
Hierarchical Object Classification for Autonomous Mobile Robots.
In J. R. Dorronsoro, editor, Artificial Neural Networks - ICANN 2002, pages 831-836, Berlin, 2002. Springer Verlag.

75

H. El-Messiry, H. A. Kestler, O. Grebe, and H. Neumann.
Morphological Scal-Space Decomposition for Segmenting the Venricular Structure in Cardiac MR Images.
In T. Wittenberg, P. Hastreiter, U. Hoppe, H. Handels, A. Horsch, and H.-P. Meinzer, editors, Bildverarbeitung für die Medizin 2003, pages 181-185, Berlin, 2003. Springer Verlag.

76

H. El-Messiry, H. A. Kestler, O. Grebe, and H. Neumann.
Segmenting the Endocardial Border of the Left Ventricle in Cardiac Magnetic Resonance Images.
IEEE Computers in Cardiology, 30:625-628, 2003.

77

O. Grebe, A. Mueller, N. Merkle, J. Wöhrle, L. Binner, V. Hombach, H. Neumann, and H. A. Kestler.
Estimation of Intra- and Inter-ventricular Dyssynchronization with Cardiac Magnetic Resonance Imaging.
IEEE Computers in Cardiology, 30:741-743, 2003.

78

H. A. Kestler and M. Höher.
Prognostic Value of Intra-QRS and ST-T Micro-Variability - A 2 Year Follow-up.
IEEE Computers in Cardiology, 30:89-92, 2003.

79

A. Mueller, N. Merkle, V. Hombach, O. Grebe, T. Nusser, J. Woehrle, L. Binner, and H. A. Kestler.
Extracting Robust Features from Cardiac Magnetic Resonance Image Contours for Detecting Dilated Cardiomyopathy.
IEEE Computers in Cardiology, 31:157-160, 2004.

80

A. Mueller, A. Neitmann, N. Merkle, J. Woehrle, V. Hombach, and H. A. Kestler.
Contour Detection of Short Axis Slice MR Images for Contraction Irregularity Assessment.
IEEE Computers in Cardiology, 32:21-24, 2005.

Book Chapters

81

H. A. Kestler.
Wörterbuch der Kognitionswissenschaft.
Klett-Cotta, Stuttgart, 1995.
Coauthor.

82

F. Schwenker, J. He, H. A. Kestler, E. Littman, S. Schieszl, and G. Palm.
Anwendungen neuronaler Netze.
In G. Bol, G. Nakhaeizadeh, and K.-H. Vollmer, editors, Finanzmarktanalyse und -prognose mit innovativen quantitativen Verfahren, pages 35-70. Physica-Verlag, 1996.

83

V. Hombach, H. A. Kestler, H. H. Osterhues, B. Scharf, M. Kochs, and M. Höher.
A Modern Approach to Risk Stratification in Patients with Structural Heart Disease.
In T. Katila and R. Maniewski, editors, Lecture Notes of the ICB Seminars 38: High-resolution Electro- and Magnetocardiography, pages 126-136. Polish Academy of Sciences, Warsaw, 1998.

84

M. Höher, S. Bauer, and H. A. Kestler.
Detection of QRS-Variability.
In H.-H. Osterhues, V. Hombach, and A. J. Moss, editors, Advances in Noninvasive Electrocardiographic Monitoring Techniques, chapter 10, pages 109-119. Kluwer Academic Publishers, Dordrecht, 2000.

85

H. A. Kestler, F. Schwenker, G. Palm, J. Wöhrle, and M. Höher.
Neural Classification in High-Resolution ECG Signal Processing.
In H.-H. Osterhues, V. Hombach, and A. J. Moss, editors, Advances in Noninvasive Electrocardiographic Monitoring Techniques, chapter 43, pages 441-452. Kluwer Academic Publishers, Dordrecht, 2000.

86

H. A. Kestler.
Lexikon der Neurowissenschaft.
Spektrum Akademischer Verlag, Heidelberg, 2000.
Coauthor.

87

V. Hombach, H.-H. Osterhues, B. Schleß, M. Kochs, H. A. Kestler, and M. Höher.
QT Dispersion: Definition, Methodology, and Clinical Relevance.
In A. Oto and G. Breithardt, editors, Myocardial Repolarization: From Gene to Bedside, chapter 10, pages 187-209. Futura Publishing Co., Armonk, 2001.

88

F. Schwenker and H. A. Kestler.
3-D Visual Object Classification with Hierarchical Radial Basis Function Networks.
In R.J. Howlett and L.C. Jain, editors, Radial Basis Function Networks 2, chapter 8, pages 269-293. Physica-Verlag, Heidelberg, 2001.

89

H. A. Kestler and F. Schwenker.
RBF Network Classification of ECGs as a Potential Marker for Sudden Cardiac Death.
In R.J. Howlett and L.C. Jain, editors, Radial Basis Function Networks 2, chapter 6, pages 167-214. Physica-Verlag, Heidelberg, 2001.

90

F. Schwenker, H. A. Kestler, and G. Palm.
Algorithms for the Visualization of Large and Multivariate Data Sets.
In U. Seiffert and L.C. Jain, editors, Self-Organizing Neural Networks, chapter 8, pages 165-183. Physica-Verlag, Heidelberg, 2002.

91

F. Schwenker, H. A. Kestler, and G. Palm.
Unsupervised and Supervised Learning in Radial-Basis-Function Networks.
In U. Seiffert and L.C. Jain, editors, Self-Organizing Neural Networks, chapter 10, pages 217-243. Physica-Verlag, Heidelberg, 2002.

92

T. Mattfeldt, H.-W. Gottfried, M. Burger, and H. A. Kestler.
Classification of Prostatic Cancer Using Artificial Neural Networks.
In G. A. Losa, D. Merlini, T. F. Nonnenmacher, and E. R. Weibel, editors, Fractals in Biology and Medicine, Volume III, pages 101-111. Birkhäuser, Basel, 2002.

93

M. Buchholz, H. A. Kestler, A. Bauer, J. D. Hoheisel, and T. M. Gress.
Development of diagnostic arrays for the differential diagnosis of a pancreatic mass.
In T. M. Gress, J. Neoptolemos, N. R. Lemoine, and F. X. Real, editors, Exocrine pancreas cancer, pages 394-401. Solvay Pharmaceuticals, 2005.

94

H. A. Kestler, R. Schuler, A. Müller, M. Buchholz, F. Schwenker, G. Palm, and T. M. Gress.
Bioinformatic methods for microarray data analysis in pancreatic cancer.
In T. M. Gress, J. Neoptolemos, N. R. Lemoine, and F. X. Real, editors, Exocrine pancreas cancer, pages 228-241. Solvay Pharmaceuticals, 2005.

95

M. Höher, H. A. Kestler, and V. Hombach.
Special computerized evaluation of high resolution electrocardiograms for risk stratification - Neural network analysis.
New Trends Arrhythm, 9(4):859-864, 1993.

96

M. Höher, H. A. Kestler, and V. Hombach.
Frequency and Wavelet Analysis of the Signal-Averaged Surface Electrocardiogram.
Annals of Noninvasive Electrocardiology, 1(3):261-263, 1996.
Editorial.

97

A. Baune, S. Simon, H. A. Kestler, F. Schwenker, and G. Palm.
Implementierungsaspekte der Objektklassifikation unter SMARTSOFT.
Ulmer SFB 527 Reports 1999/10, University of Ulm, Germany, 1999.
ISSN 1438-2237.

98

S. Simon, H. A. Kestler, A. Baune, F. Schwenker, and G. Palm.
Werkzeuge zur visuellen Objektklassifikation.
Ulmer SFB 527 Reports 1999/3, University of Ulm, Germany, 1999.
ISSN 1438-2237.

99

H. A. Kestler.
Calculation and Display of Confidence Bounds for Receiver Operator Characteristics.
Methods of Information in Medicine, 38(1):74, 1999.
Letter to the Editor.

100

H. A. Kestler, S. Simon, A. Baune, F. Schwenker, and G. Palm.
Object classification using simple, colour based visual attention and a hierarchical neural network for neural-symbolic integration.
Ulmer SFB 527 Reports 1999/4, University of Ulm, Germany, 1999.
ISSN 1438-2237.

101

H. A. Kestler, G. Mayer, and H. Neumann.
Ansätze der Clusterbasierten Objektverfolgung auf einem mobilen Roboter.
Ulmer SFB 527 Reports 1999/5, University of Ulm, Germany, 1999.
ISSN 1438-2237.

102

H. A. Kestler, M. Borst, and H. Neumann.
Einfache Handgestikerkennung mit einem zweistufigen Nearest-neighbour Klassifikator.
Ulmer SFB 527 Reports 1999/6, University of Ulm, Germany, 1999.
ISSN 1438-2237.

103

H. A. Kestler.
Per(l)formance Evaluation of Classifiers - Using Perl for Simulation.
In J. Christoffel, editor, GMD Report 49: Erster Deutscher Perl-Workshop 1.0. GMD - Forschungszentrum Informationstechnik GmbH, 1999.

104

H. A. Kestler.
Annual Review of Biomedical Engineering Volume 1, 1999.
Medical & Biological Engineering & Computing, pages N14-N16, May 2000.
Book review.

105

F. Schwenker, H. A. Kestler, and G. Palm.
3-D Visual Object Classification with Hierarchical Radial Basis Function Networks.
Ulmer Informatik-Berichte 2001-02, University of Ulm, Germany, 2001.
ISSN 0939-5091.

106

H. A. Kestler, F. Schwenker, and G. Palm.
RBF network classification of ECGs as a potential marker for sudden cardiac death.
Ulmer Informatik-Berichte 2001-03, University of Ulm, Germany, 2001.
ISSN 0939-5091.

107

H. A. Kestler, A. Müller, H. Liu, D. W. Kane, B. W. Zeeberg, and J. N. Weinstein.
Euler diagrams for visualizing annotated gene expression data.
In A. Verroust-Blondet and M.-L. Viaud, editors, Euler Diagrams 2005, pages 1-4. INRIA, INA, Paris, France, 2005.

108

H. A. Kestler.
Numerische Lösung dynamischer Optimierungsaufgaben mittels Algorithmen der nichtlinearen Programmierung.
Studienarbeit 844, Lehrstuhl für Steuerungs- und Regelungstechnik, Technische Universität München, 1989.

109

H. A. Kestler.
Untersuchung und Simulation von selbstoptimierenden Neuronalen Netzen.
Diplomarbeit, Technische Universität München, Lehrstuhl für Integrierte Schaltungen, December 1991.

110

H. A. Kestler.
Analysis of High-Resolution Electrocardiograms - Feature Extraction and Pattern Recognition.
Dissertation, Universität Ulm, Abteilung Neuroinformatik, July 2002.