Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2005-04-19
2005-04-19
Patel, Ramesh (Department: 2121)
Data processing: artificial intelligence
Neural network
Learning task
C706S012000
Reexamination Certificate
active
06882990
ABSTRACT:
Systems and methods for enhancing knowledge discovery from data using multiple learning machines in general and multiple support vector machines in particular. Training data for a learning machine is pre-processed in order to add meaning thereto. Multiple support vector machines, each comprising distinct kernels, are trained with the pre-processed training data and are tested with test data that is pre-processed in the same manner. The test outputs from multiple support vector machines are compared in order to determine which of the test outputs if any represents a optimal solution. Selection of one or more kernels may be adjusted and one or more support vector machines may be retrained and retested. Optimal solutions based on distinct input data sets may be combined to form a new input data set to be input into one or more additional support vector machine. The methods, systems and devices of the present invention comprise use of Support Vector Machines for the identification of patterns that are important for medical diagnosis, prognosis and treatment. Such patterns may be found in many different datasets. The present invention also comprises methods and compositions for the treatment and diagnosis of medical conditions.
REFERENCES:
patent: 4881178 (1989-11-01), Holland et al.
patent: 5138694 (1992-08-01), Hamilton
patent: 5649068 (1997-07-01), Boser et al.
patent: 5809144 (1998-09-01), Sirbu et al.
patent: 5950146 (1999-09-01), Vapnik
patent: 6128608 (2000-10-01), Barnhill
patent: 6157921 (2000-12-01), Barnhill
patent: 6427141 (2002-07-01), Barnhill
patent: 6714925 (2004-03-01), Barnhill et al.
patent: 6760715 (2004-07-01), Barnhill et al.
“Prior Knowledge in Support Vector Kernels” Bernhard Scholkopf, Patrice Simard, Alex Smola & Vladimir Vapnik (1998).*
Yan, Yonghong et al., “Experiments for an approach to language identification with conversational telephone speech” 1995 IEEE International Conference, pp. 789-792.
Osuna, Edgar et al., “An Improved Training Algorithm for Support Vector Machines”, 1997 IEEE International Conference, pp. 276-285.
Osuna, Edgar et al., “Training Support Vector Machines: an Application to Face Detection”, 1997 IEEE Conference, pp. 130-136.
Osuna, Edgar et al., “Support Vector Machines: Training and Applications”, Massachusetts Institute of Technology, Artificial Intelligence Laboratory and Center for Biological and Computational Learning Department of Brain and Cognitive Sciences, Copyright 1996, Published Mar. 1997, pp. 1-41.
Pontil, Massimiliano et al., “Properties of Support Vector Machines”, Massachusetts Institute of Technology, Artificial Intelligence Laboratory and Center for Biological and Computational Learning Department of Brain and Cognitive Sciences, Copyright 1999, Published Aug. 1997, 1994, pp. 1-6.
Sung, Kah-Kay et al., “Example-based Learning for View-based Human Face Detection”, Massachusetts Institute of Technology, Artificial Intelligence Laboratory and Center for Biological and Computational Learning Department of Brain and Cognitive Sciences, Copyright 1994, Published Dec. 1994, pp. 1-16.
Alpaydin, Ethem, “Multiple Neural Networks and Weighted Voting”, 1992 IEEE, Department of Computer Engineering, Bogazici University, pp. 29-32.
Kim, Jongryeol et al., “A Systematic Approach to Classifier Selection on Combining Multiple Classifiers for Handwritten Digit Recognition”, 1997 IEEE, Soongsil University, pp. 459-461.
Kato, Yoshinaga et al., “An Application of SVM: Alphanumeric Character Recognition”, IEEE International Joint Conference on Neural Networks, Jun. 1989 (Abstract only).
Scholkopf, Bernhard et al., “Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers”, IEEE Transactions on Signal Processing, vol. 45, No. 11, Nov. 1997, pp. 2758-2765.
de Chazal, P et al., “Improving ECG Diagnostic Classification by Combining Multiple Neural Networks”, 1997 IEEE, Computers in Cardiology, vol. 24, 1997, pp. 473-476.
U.S. Appl. 09/303,389 filed May 1, 1999; Inventor: Stephen Barnhill; entitled: “Optimal Categorization of a Continuous Variable”.
U.S. Appl. 09/305,345 filed May 1, 1999; Inventor: Stephen Barnhill; entitled: “Enhancing Knowledge Discovery Using Support Vector Machines in a Distributed Network Environment”.
U.S. Appl. 09/303,386 filed Nov. 17, 2000; Inventor: Stephen Barnhill entitled: “Pre-Processing and Post Processing for Enhancing Knowledge Discovery Using Support Vector Machines”.
U.S. Appl. 09/568,301 filed May 9, 2000; Inventor: Stephen Barnhill; entitled: Enhancing Knowledge Discovery Using Multiple Support Vector Machines.
U.S. Appl. 09/578,011 filed May 24, 2000; Inventor: Stephen Barnhill; entitled “Enhancing Knowledge Discovery from Multiple Data Sets Using Multiple Support Vector”.
Brown, Michael S., et al. “Knowledge-based analysis of microarray gene expression data by using support vector machines”, PNAS, vol. 97, Jan. 4, 2000, pp. 262-267.
Alon, U., et al., “Broad patterns of gene expression revealed by clustering analysis of tumor normal colon tissues probed by oligonucleotide arrays”, PNAS, vol. 96, Jun. 1999, pp. 6745-6750 (Abstract only).
Eisen, M. B., et al., “Cluster analysis and display of genome-wide expression pattersn”, Proc. Natl. Acad. Sci. USA, vol. 95, Dec. 1998, pp. 14863-14868 (Abstract only).
Golub, T.R., et al., “Molecular classification of cancer: class discovery and class prediction by gene expression monitoring”, Science, vol. 286, Oct. 1999, pp. 531-537 (Abstract only).
Alizadeh, A.A., et al., “Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling”, Nature, vol. 403, Issued 3, Feb. 2000, pp. 503-511 (Abstract only).
Thorsteinsdottir, U., et al., “The oncoprotein E2A-Pbx1A collaborates with Hoxa9 to acutely transform primary bone marrow cells”, Molecular Cell Biology, vol. 19, Issue 9, Sep. 1999, pp. 6355-6366 (Abstract only).
Osaka, M., et al., “MSF (MLL septin-like fusion), a fusion partner gene of MLL, in a therapy-related acute myeloid leukemia with a t(II, 17)(q23:125)”, Proc. Natl. Acad. Sci. USA, vol. 96, Issue 11, May 1999, pp. 6428-6433 (Abstract only).
Macaima, T., et al., “Molecular characterization of human zyxin”, Journal of Biological Chemistry, vol. 271, Issue 49, Dec. 1996, pp. 31470-31478 (Abstract only).
Harlan, D.M., et al., “The human myristoylated alanine rich C kinase substrate (MARCKS) gene (MACS). Analysis of its gene product, promoter, and chromosomal localization”, Journal of Biological Chemistry, vol. 266, Issue 12, Aug. 1991, pp. 14399-14405 (Abstract only).
Moser, T.L., et al., “Angioslatin binds ATP Synthase on the surface of human endothelial cells”, PNAS, vol. 96, Issue 6, Mar. 1999, pp. 2811-2816 (Abstract only).
Karakiulakis, G., et al., “Increased type IV collagen-degrading activity in metastases originating from primary tumors of the human colon”, Invasion and Metastasis, vol. 17, No. 3, 1997, pp. 158-168 (Abstract only).
Ghigna, C., et al., “Altered expression of heterogenous nuclear ribonucleoproteins and SR factors in human colon adenocarcinomas”, Cancer Research, vol. 58, Dec. 1998, pp. 5818-5824 (Abstract only).
Perou, C.M., et al., “Distinctive gene expression patterns in human mammary cell epithelial cells and breast cancers”, Proc. Natl. Acad. Sci. USA, vol. 96, Aug. 1999, pp. 9212-9217 (Abstract only).
Barnhill Stephen
Guyon Isabelle
Weston Jason
Biowulf Technologies, LLC
Holmes Michael B.
Patel Ramesh
Procopio Cory Hargreaves & Savitch
LandOfFree
Methods of identifying biological patterns using multiple... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Methods of identifying biological patterns using multiple..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Methods of identifying biological patterns using multiple... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3373802