Patents by Inventor Carsten Peterson
Carsten Peterson has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20140221234Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: ApplicationFiled: December 30, 2013Publication date: August 7, 2014Applicant: Government of the United States Represented by the Secretary, Department of Health and Human ServiceInventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Patent number: 8620592Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: GrantFiled: October 31, 2011Date of Patent: December 31, 2013Assignee: The United States of America Represented by the Secretary, Department of Health and Human ServicesInventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Patent number: 8263759Abstract: A method of diagnosing a disease that includes obtaining experimental data on gene selections. The gene selection functions to characterize a cancer when the expression of that gene selection is compared to the identical selection from a noncancerous cell or a different type of cancer cell. The invention also includes a method of targeting at least one product of a gene that includes administration of a therapeutic agent. The invention also includes the use of a gene selection for diagnosing a cancer.Type: GrantFiled: October 30, 2007Date of Patent: September 11, 2012Assignee: The United States of America, as Represented by the Secretary, Department of Health and Human ServicesInventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Publication number: 20120046878Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: ApplicationFiled: October 31, 2011Publication date: February 23, 2012Applicants: SERVICESInventors: JAVED KHAN, MARKUS RINGNÉR, CARSTEN PETERSON, PAUL MELTZER
-
Patent number: 8065092Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: GrantFiled: August 18, 2010Date of Patent: November 22, 2011Assignee: The United States of America as represented by the Department of Health and Human ServicesInventors: Javed Khan, Markus Ringnér, Carsten Peterson, Paul Meltzer
-
Publication number: 20100312486Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: ApplicationFiled: August 18, 2010Publication date: December 9, 2010Applicant: Government of the USA represented by the Secretary Dept. of Health and Human ServicesInventors: Javed Khan, Markus Ringnér, Carsten Peterson, Paul Meltzer
-
Patent number: 7783431Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: GrantFiled: October 30, 2007Date of Patent: August 24, 2010Assignee: The United States of America as represented by the Department of Health and Human ServicesInventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Patent number: 7774143Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: GrantFiled: April 25, 2002Date of Patent: August 10, 2010Assignee: The United States of America as represented by the Secretary, Department of Health and Human ServicesInventors: Javed Khan, Markus Ringnér, Carsten Peterson, Paul Meltzer
-
Patent number: 7655397Abstract: A method of diagnosing a disease that includes obtaining experimental data on gene selections. The gene selection functions to characterize a cancer when the expression of that gene selection is compared to the identical selection from a noncancerous cell or a different type of cancer cell. The invention also includes a method of targeting at least one product of a gene that includes administration of a therapeutic agent. The invention also includes the use of a gene selection for diagnosing a cancer.Type: GrantFiled: May 31, 2002Date of Patent: February 2, 2010Assignee: The United States of America as represented by the Department of Health and Human ServicesInventors: Javed Khan, Markus Ringnér, Carsten Peterson, Paul Meltzer
-
Publication number: 20090035766Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: ApplicationFiled: October 30, 2007Publication date: February 5, 2009Applicants: SERVICESInventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Publication number: 20080181896Abstract: A method of diagnosing a disease that includes obtaining experimental data on gene selections. The gene selection functions to characterize a cancer when the expression of that gene selection is compared to the identical selection from a noncancerous cell or a different type of cancer cell. The invention also includes a method of targeting at least one product of a gene that includes administration of a therapeutic agent. The invention also includes the use of a gene selection for diagnosing a cancer.Type: ApplicationFiled: October 30, 2007Publication date: July 31, 2008Applicants: DEPARTMENT OF HEALTH AND HUMAN SERVICESInventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Patent number: 6859736Abstract: This invention provides a method for protein structure alignment. More particularly, the present invention provides a method for identification, classification and prediction of protein structures. The present invention involves two key ingredients. First, an energy or cost function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. Second, a minimization of the energy or cost function by an iterative method, where in each iteration (1) a mean field method is employed for the assignment variables and (2) exact rotation and/or translation of atomic coordinates is performed, weighted with the corresponding assignment variables.Type: GrantFiled: April 2, 2001Date of Patent: February 22, 2005Assignee: The Board of Trustees of the Lealand Stanford Junior UniversityInventors: Richard Blankenbecler, Mattias Ohlsson, Carsten Peterson, Markus Ringner
-
Publication number: 20040199481Abstract: An optimization system is provided utilizing a Bayesian neural network calculation of a derivative wherein an output is optimized with respect to an input utilizing a stochastical method that averages over many regression models. This is done such that constraints from first principal models are incorporated in terms of prior art distributions.Type: ApplicationFiled: April 20, 2004Publication date: October 7, 2004Inventors: Eric Jon Hartman, Carsten Peterson, Stephen Piche
-
Patent number: 6725208Abstract: An optimization system is provided utilizing a Bayesian neural network calculation of a derivative wherein an output is optimized with respect to an input utilizing a stochastical method that averages over many regression models. This is done such that constraints from first principal models are incorporated in terms of prior art distributions.Type: GrantFiled: April 12, 1999Date of Patent: April 20, 2004Assignee: Pavilion Technologies, Inc.Inventors: Eric Jon Hartman, Carsten Peterson, Stephen Piche
-
Publication number: 20040009154Abstract: A method of diagnosing a disease that includes obtaining experimental data on gene selections. The gene selection functions to characterize a cancer when the expression of that gene selection is compared to the identical selection from a noncancerous cell or a different type of cancer cell. The invention also includes a method of targeting at least one product of a gene that includes administration of a therapeutic agent. The invention also includes the use of a gene selection for diagnosing a cancer.Type: ApplicationFiled: May 31, 2002Publication date: January 15, 2004Inventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Publication number: 20030207278Abstract: A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.Type: ApplicationFiled: April 25, 2002Publication date: November 6, 2003Inventors: Javed Khan, Markus Ringner, Carsten Peterson, Paul Meltzer
-
Publication number: 20020111781Abstract: This invention provides a method for protein structure alignment. More particularly, the present invention provides a method for identification, classification and prediction of protein structures. The present invention involves two key ingredients. First, an energy or cost function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. Second, a minimization of the energy or cost function by an iterative method, where in each iteration (1) a mean field method is employed for the assignment variables and (2) exact rotation and/or translation of atomic coordinates is performed, weighted with the corresponding assignment variables.Type: ApplicationFiled: April 2, 2001Publication date: August 15, 2002Inventors: Richard Blankenbecler, Mattias Ohlsson, Carsten Peterson, Markus Ringner
-
Patent number: 5956413Abstract: In automatic evaluation of cereal kernels or like granular products handled in bulk, the kernels are conveyed on a vibrating conveyor belt (15). Owing to the vibrations, the kernels are spread and settled in grooves (14) in the belt so as to be oriented in essentially the same direction. A video camera (40) produces digital images of all the kernels on the belt. The kernels are identified in the images, and for each kernel input signals are produced and then sent to a neural network based on picture element values for the picture elements representing each kernel. A neural network then determines which of a plurality of predetermined classes that each kernel belongs.Type: GrantFiled: December 23, 1997Date of Patent: September 21, 1999Assignee: Agrovision ABInventors: Rickard Oste, Peter Egelberg, Carsten Peterson, Patrik Soderlund, Lennart Sjostedt
-
Patent number: 5898792Abstract: The flour yield, protein content and bulk density of cereal kernels can be determined by producing images of the cereal kernels, at least one color parameter and/or at least one geometric parameter are determined for the cereal kernels, and input signals to a neural network are produced by means of the color parameter and/or the geometric parameter. If the neural network is trained in some suitable manner, it can determine the flour yield, protein content and bulk density on the basis of the input signals.Type: GrantFiled: November 5, 1996Date of Patent: April 27, 1999Assignee: Agrovision ABInventors: Rickard Oste, Peter Egelberg, Carsten Peterson, Eivor Svensson, Olle M.o slashed.nsson
-
Patent number: 5640966Abstract: An analysis apparatus such as an ECG apparatus has a control unit which includes an artificial neural network for discovering signal-recording electrodes which are erroneously attached to a patient. At least one artificial neural network is taught by being fed measurement signals from both correctly recorded measurements and from erroneously recorded measurements. The artificial neural network is then able to identify erroneous attachments with great accuracy from recorded measurement signals.Type: GrantFiled: November 6, 1995Date of Patent: June 24, 1997Assignee: Siemens Elema ABInventors: Bo Heden, Mattias Ohlsson, Lars Edenbrandt, Ralf Rittner, Olle Pahlm, Carsten Peterson