Patents by Inventor Justin Bedo
Justin Bedo 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).
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Publication number: 20230417777Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: ApplicationFiled: January 27, 2023Publication date: December 28, 2023Inventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Publication number: 20200088747Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: ApplicationFiled: April 9, 2019Publication date: March 19, 2020Inventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Patent number: 9922058Abstract: This disclosure is related to further approximating multiple data vectors of a dataset. The multiple data vectors are initially approximated by one or more stored principle components. A processor performs multiple iterations of determining an updated estimate of a further principle component based on the multiple data vectors that are initially approximated by the one or more stored principle components. The processor performs this step such that the updated estimate of the further principal component further approximates the dataset. In each iteration the processor constrains the updated estimate of the further principal component to be orthogonal to each of the one or more stored principal components. The data vectors of the dataset are not manipulated but remain the same data vectors that are approximated by the stored principal components.Type: GrantFiled: July 16, 2014Date of Patent: March 20, 2018Assignee: NATIONAL ICT AUSTRALIA LIMITEDInventors: Justin Bedo, Adam Kowalczyk, Karin Klotzbuecher
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Publication number: 20160131667Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: ApplicationFiled: January 19, 2016Publication date: May 12, 2016Inventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Patent number: 9255935Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: GrantFiled: June 30, 2015Date of Patent: February 9, 2016Assignee: BAKER IDI HEART AND DIABETES INSTITUTE HOLDINGS LIMITEDInventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Publication number: 20150301070Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: ApplicationFiled: June 30, 2015Publication date: October 22, 2015Inventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Patent number: 9110086Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: GrantFiled: November 26, 2010Date of Patent: August 18, 2015Assignee: BAKER IDI HEART AND DIABETES INSTITUTE HOLDINGS LIMITEDInventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Publication number: 20150026134Abstract: This disclosure is related to further approximating multiple data vectors of a dataset. The multiple data vectors are initially approximated by one or more stored principle components. A processor performs multiple iterations of determining an updated estimate of a further principle component based on the multiple data vectors that are initially approximated by the one or more stored principle components. The processor performs this step such that the updated estimate of the further principal component further approximates the dataset. In each iteration the processor constrains the updated estimate of the further principal component to be orthogonal to each of the one or more stored principal components. The data vectors of the dataset are not manipulated but remain the same data vectors that are approximated by the stored principal components.Type: ApplicationFiled: July 16, 2014Publication date: January 22, 2015Inventors: Justin Bedo, Adam Kowalczyk, Karin Klotzbuecher
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Publication number: 20130198118Abstract: A computer-implemented method for annotation of a biological sequence, comprising: applying a classifier to determine a label for the first segment of a first biological sequence of a first species based on an estimated relationship between second segments in a training set and known labels of the second segments in the training set. The classifier is trained using the training set to estimate the relationship, and the second segments are of a second biological sequence of a second species that is different to, or a variant of, the first species. This disclosure also concerns a computer program and a computer system for annotation of a biological sequence.Type: ApplicationFiled: March 8, 2011Publication date: August 1, 2013Inventors: Adam Kowalczyk, Justin Bedo, Izhak Haviv
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Publication number: 20130132331Abstract: A computer-implemented method for evaluating performance of a classifier, the method comprising: (a) comparing labels determined by the classifier with corresponding known labels; and (b) based on the comparison, estimating a probability of observing an equal or better precision at a given recall with random ordering of the labels determined by the classifier. This disclosure also concerns a computer program and a computer system for evaluating performance of a classifier.Type: ApplicationFiled: March 8, 2011Publication date: May 23, 2013Applicant: NATIONAL ICT AUSTRALIA LIMITEDInventors: Adam Kowalczyk, Justin Bedo, Izhak Haviv
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Publication number: 20130023054Abstract: The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.Type: ApplicationFiled: November 26, 2010Publication date: January 24, 2013Applicant: Baker IDI Heart and Diabetes Institute Holdings LimitedInventors: Peter John Meikle, Izhak Haviv, Bronwyn Anne Kingwell, Justin Bedo, Benjamin Goudey
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Patent number: 7966268Abstract: A method of assessing a signal to identify particular signal characteristics comprises application of machine learning to multi-dimensional histograms derived from multi-tap sampling of the signal. The signal is sampled from at least two tap points to retrieve a sample set, and the at least two tap points are adapted to retrieve distinct samples from the signal, such as time spaced samples or spectrally distinct samples. Multiple sample sets are retrieved from the signal over time. The at least two dimensional histogram is built from the joint probability distribution of the plurality of sample sets. A machine learning algorithm then processes the multi-dimensional histogram, and is trained to predict a value of at least one characteristic of the signal.Type: GrantFiled: October 13, 2006Date of Patent: June 21, 2011Assignee: National ICT Australia LimitedInventors: Trevor Anderson, Sarah Dods, Adam Kowalczyk, Justin Bedo, Kenneth Paul Clarke
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Patent number: 7899324Abstract: Monitoring an optical signal comprises sampling the optical signal from two or more distinct tap points to retrieve a sample set. Multiple such sample sets are obtained over time. A joint probability distribution or phase portrait of the sample sets is assessed for indications of optical signal quality. The tap distinction can be polarization, for example to determine OSNR, or frequency. The tap distinction can be a time delay, which can enable diagnostic differentiation between multiple impairments, such as OSNR, dispersion, PMD, jitter, Q, and the like. Machine learning algorithms are particularly suitable for such diagnosis, particularly when provided a two dimensional histogram of sample density in the phase portrait.Type: GrantFiled: October 13, 2006Date of Patent: March 1, 2011Assignee: Nicta IPR Pty LimitedInventors: Trevor Anderson, Sarah Dods, Adam Kowalczyk, Justin Bedo, Kenneth Paul Clarke
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Publication number: 20100042559Abstract: A method of assessing a signal to identify particular signal characteristics comprises application of machine learning to multi-dimensional histograms derived from multi-tap sampling of the signal. The signal is sampled from at least two tap points to retrieve a sample set, and the at least two tap points are adapted to retrieve distinct samples from the signal, such as time spaced samples or spectrally distinct samples. Multiple sample sets are retrieved from the signal over time. The at least two dimensional histogram is built from the joint probability distribution of the plurality of sample sets. A machine learning algorithm then processes the multi-dimensional histogram, and is trained to predict a value of at least one characteristic of the signal.Type: ApplicationFiled: October 13, 2006Publication date: February 18, 2010Applicant: National ICT Australia LimitedInventors: Trevor Anderson, Dods Sarah, Adam Kowalczyk, Justin Bedo, Kenneth Paul Clarke
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Publication number: 20090028554Abstract: Monitoring an optical signal comprises sampling the optical signal from two or more distinct tap points to retrieve a sample set. Multiple such sample sets are obtained over time. A joint probability distribution or phase portrait of the sample sets is assessed for indications of optical signal quality. The tap distinction can be polarisation, for example to determine OSNR, or frequency. The tap distinction can be a time delay, which can enable diagnostic differentiation between multiple impairments, such as OSNR, dispersion, PMD, jitter, Q, and the like. Machine learning algorithms are particularly suitable for such diagnosis, particularly when provided a two dimensional histogram of sample density in the phase portrait.Type: ApplicationFiled: October 13, 2006Publication date: January 29, 2009Applicant: NATIONAL ICT AUSTRALIA LIMITEDInventors: Trevor Anderson, Sarah Dods, Adam Kowalczyk, Justin Bedo, Kenneth Paul Clarke