Patents by Inventor James S. Burns
James S. Burns 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: 20220020466Abstract: Methods comprising an integrated, multiscale artificial intelligence-based system that reconstructs drug-specific pharmacogenomic networks and their constituent functional sub-networks are described. The system uses features of the functional topology of the three-dimensional architecture of drug-modulated spatial contacts in chromatin space. Discovery of a drug pharmacogenomic network is made through the selection of candidate SNPs by imputation, determination of the predicted causality of the SNPs using machine learning and deep learning, use of the causal SNPs to probe the spatial genome as determined by chromosome conformation capture analysis, combining targeted genes controlled by the same cell and tissue-specific enhancers, and reconstruction of the pharmacogenomic network using diverse data sources and metrics based on the results of genome-wide association studies.Type: ApplicationFiled: September 22, 2021Publication date: January 20, 2022Inventors: Brian D. Athey, Gerald A. Higgins, Alex Ade, Alexandr Kalinin, Narathip Reamaroon, James S. Burns
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Patent number: 10867702Abstract: For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc., to benefit from additional predictive power, resulting in adverse event and substance abuse avoidance, improved drug response, better patient outcomes, lower treatment costs, public health benefits, and increases in the effectiveness of research in pharmacology and other biomedical fields.Type: GrantFiled: December 23, 2019Date of Patent: December 15, 2020Assignee: THE REGENTS OF THE UNIVERSITY OF MICHIGANInventors: Brian D. Athey, Ari Allyn-Feuer, Gerald A. Higgins, James S. Burns, Alexandr Kalinin, Brian Pauls, Alex Ade, Narathip Reamaroon
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Publication number: 20200294623Abstract: Methods comprising an integrated, multiscale artificial intelligence-based system that reconstructs drug-specific pharmacogenomic networks and their constituent functional sub-networks are described. The system uses features of the functional topology of the three-dimensional architecture of drug-modulated spatial contacts in chromatin space. Discovery of a drug pharmacogenomic network is made through the selection of candidate SNPs by imputation, determination of the predicted causality of the SNPs using machine learning and deep learning, use of the causal SNPs to probe the spatial genome as determined by chromosome conformation capture analysis, combining targeted genes controlled by the same cell and tissue-specific enhancers, and reconstruction of the pharmacogenomic network using diverse data sources and metrics based on the results of genome-wide association studies.Type: ApplicationFiled: January 22, 2020Publication date: September 17, 2020Inventors: Brian D. Athey, Gerald A. Higgins, Alex Ade, Alexandr Kalinin, Narathip Reamaroon, James S. Burns
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Publication number: 20200234810Abstract: Methods for identifying patients diagnosed with treatment resistant or refractory depression, pain or other clinical indications who are eligible to receive N-methyl-D-aspartate receptor antagonist, glycine receptor beta (GLRB) modulator, or ?-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-based therapies to include determining the appropriate medication, an optimal dose for each patient, and determining which patients are not eligible to receive the therapy. The pharmacogenomic clinical decision support assays include targeted single nucleotide polymorphisms and clinical values or a combination of targeted single nucleotide polymorphisms, targeted ketamine-specific expansion and contraction of topologically associated domains, and clinical values. The methods described herein allow for a more effective determination of which patients will experience drug efficacy and which patients will experience adverse drug events.Type: ApplicationFiled: January 22, 2020Publication date: July 23, 2020Inventors: Brian D. Athey, Alex Ade, Gerald A. Higgins, Alexandr Kalinin, Narathip Reamaroon, James S. Burns
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Publication number: 20200233410Abstract: Aspects of the present disclosure generally pertains to freight trailers having onboard power. Aspects of the present disclosure more specifically are directed toward an electric freight trailer that can recycle the trailer braking energy of the towing vehicle, and also provide additional thrust to propel the freight trailer. Aspects of the present disclosure are also directed toward an electric freight trailer that can propel itself independently of a tractor, including steering and braking. Aspects of the disclosure are also directed toward additional subsystems that can utilize the trailer energy source.Type: ApplicationFiled: January 22, 2020Publication date: July 23, 2020Inventors: James S. BURNS, Thomas L. BARTLEY
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Publication number: 20200135337Abstract: For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc., to benefit from additional predictive power, resulting in adverse event and substance abuse avoidance, improved drug response, better patient outcomes, lower treatment costs, public health benefits, and increases in the effectiveness of research in pharmacology and other biomedical fields.Type: ApplicationFiled: December 23, 2019Publication date: April 30, 2020Inventors: Brian D. Athey, Ari Allyn-Feuer, Gerald A. Higgins, James S. Burns, Alexandr Kalinin, Brian Pauls, Alex Ade, Narathip Reamaroon
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Patent number: 10553318Abstract: For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc., to benefit from additional predictive power, resulting in adverse event and substance abuse avoidance, improved drug response, better patient outcomes, lower treatment costs, public health benefits, and increases in the effectiveness of research in pharmacology and other biomedical fields.Type: GrantFiled: February 5, 2019Date of Patent: February 4, 2020Assignee: THE REGENTS OF THE UNIVERSITY OF MICHIGANInventors: Brian D. Athey, Ari Allyn-Feuer, Gerald A. Higgins, James S. Burns, Alexandr Kalinin, Brian Pauls, Alex Ade, Narathip Reamaroon
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Patent number: 10344583Abstract: Provided is an acoustic housing including a cover including a first perimeter defining an open cover portion, the cover having a cover length, and a cover height, and a body including a second perimeter defining an open body portion, wherein either the first or second or both perimeters are chamfered, configured to receive one or more electrical components and to sealingly engage with the first chamfered perimeter, the body having a body length, a body height, and an under-surface, and the body including an engagement portion projecting from the under-surface and having an engagement length, an engagement height, and an engagement surface configured to engage an outer surface of a tubular.Type: GrantFiled: August 29, 2017Date of Patent: July 9, 2019Assignee: ExxonMobil Upstream Research CompanyInventors: Katie M. Walker, Thomas M. Smith, Henry Alan Wolf, James S. Burns, Timothy R. Bragg, Mark M. Disko, Yibing Zhang
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Publication number: 20190172584Abstract: For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc., to benefit from additional predictive power, resulting in adverse event and substance abuse avoidance, improved drug response, better patient outcomes, lower treatment costs, public health benefits, and increases in the effectiveness of research in pharmacology and other biomedical fields.Type: ApplicationFiled: February 5, 2019Publication date: June 6, 2019Inventors: Brian D. Athey, Ari Allyn-Feuer, Gerald A. Higgins, James S. Burns, Alexandr Kalinin, Brian Pauls, Alex Ade, Narathip Reamaroon
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Patent number: 10249389Abstract: For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic, physiomic, environmental, sociomic, demographic, and outcome phenotype data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc.Type: GrantFiled: May 11, 2018Date of Patent: April 2, 2019Assignee: THE REGENTS OF THE UNIVERSITY OF MICHIGANInventors: Brian D. Athey, Ari Allyn-Feuer, Gerald A. Higgins, James S. Burns, Alexandr Kalinin, Brian Pauls, Alex Ade, Narathip Reamaroon
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Publication number: 20180330824Abstract: For patients who exhibit or may exhibit primary or comorbid disease, pharmacological phenotypes may be predicted through the collection of panomic, physiomic, environmental, sociomic, demographic, and outcome phenotype data over a period of time. A machine learning engine may generate a statistical model based on training data from training patients to predict pharmacological phenotypes, including drug response and dosing, drug adverse events, disease and comorbid disease risk, drug-gene, drug-drug, and polypharmacy interactions. Then the model may be applied to data for new patients to predict their pharmacological phenotypes, and enable decision making in clinical and research contexts, including drug selection and dosage, changes in drug regimens, polypharmacy optimization, monitoring, etc.Type: ApplicationFiled: May 11, 2018Publication date: November 15, 2018Inventors: Brian D. Athey, Ari Allyn-Feuer, Gerald A. Higgins, James S. Burns, Alexandr Kalinin, Brian Pauls, Alex Ade, Narathip Reamaroon
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Patent number: 10100635Abstract: A system for downhole telemetry is provided herein. The system employs a series of communications nodes spaced along a tubular body in a wellbore. Each communications node is associated with a sensor that senses data indicative of a formation condition or a wellbore parameter along a subsurface formation. The data is stored in memory until a logging tool is run into the wellbore. The data is transmitted from the respective communications nodes to a receiver in the logging tool. The data is then transferred to the surface. A method of transmitting data in a wellbore is also provided herein. The method uses a logging tool to harvest data in a wellbore from a plurality of sensor communications nodes.Type: GrantFiled: December 18, 2013Date of Patent: October 16, 2018Assignee: ExxonMobil Upstream Research CompanyInventors: Stuart R. Keller, Timothy I. Morrow, James S. Burns, Max Deffenbaugh, Mark M. Disko, David A. Stiles
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Publication number: 20180066510Abstract: Provided is an acoustic housing including a cover including a first perimeter defining an open cover portion, the cover having a cover length, and a cover height, and a body including a second perimeter defining an open body portion, wherein either the first or second or both perimeters are chamfered, configured to receive one or more electrical components and to sealingly engage with the first chamfered perimeter, the body having a body length, a body height, and an under-surface, and the body including an engagement portion projecting from the under-surface and having an engagement length, an engagement height, and an engagement surface configured to engage an outer surface of a tubular.Type: ApplicationFiled: August 29, 2017Publication date: March 8, 2018Inventors: Katie M. Walker, Thomas M. Smith, Henry Alan Wolf, James S. Burns, Timothy R. Bragg, Mark M. Disko, Yibing Zhang
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Patent number: 9644466Abstract: A method of recovering hydrocarbons includes forming a first electrode by creating a first hydraulic fracture within the subsurface formation and pumping a first electrically conductive material into the first hydraulic fracture; forming a second electrode by creating a second hydraulic fracture within the subsurface formation and pumping a second electrically conductive material into the second hydraulic fracture; electrically connecting a first power transmitting mechanism to the first electrode; electrically connecting a second power transmitting mechanism to the second electrode; and heating the subsurface formation between the first electrode and the second electrode by transmitting an electrical current via the first power transmitting mechanism to the first electrode and via the second power transmitting mechanism to the second electrode and by flowing the electrical current from the first electrode to the second electrode.Type: GrantFiled: October 15, 2015Date of Patent: May 9, 2017Assignee: ExxonMobil Upstream Research CompanyInventors: William A. Symington, Erik H Clayton, Robert D. Kaminsky, Larry J Manak, James S. Burns
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Patent number: 9568978Abstract: Since the maximum power consumption is largely a concern at the power supply domain, a limited number of nodes may be allowed to consume their maximum power consumption by preventing other nodes from consuming their maximum power consumption. This approach may be used either instead of or in cooperation with existing maximum power consumption regulators.Type: GrantFiled: September 26, 2013Date of Patent: February 14, 2017Assignee: Intel CorporationInventors: James S. Burns, James W. Alexander, Muralidhar Rajappa
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Patent number: 9557804Abstract: A method and apparatus for dynamic power limit sharing among the modules in the platform. In one embodiment of the invention, the platform comprises a processor and memory modules. By expanding the power domain to include the processor and the memory modules, dynamic sharing of the power budget of the platform between the processor and the memory modules is enabled. For low-bandwidth workloads, the dynamic sharing of the power budget offers significant opportunity for the processor to increase its frequency by using the headroom in the memory power and vice versa. This enables higher peak performance for the same total platform power budget in one embodiment of the invention.Type: GrantFiled: September 28, 2015Date of Patent: January 31, 2017Assignee: Intel CorporationInventors: Ankush Varma, Krishnakanth V. Sistla, Cesar A. Quiroz, Vivek Garg, Martin T. Rowland, Inder M. Sodhi, James S. Burns
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Patent number: 9547027Abstract: In one embodiment, the present invention includes a processor having multiple cores to independently execute instructions, a first sensor to measure a first power consumption level of the processor based at least in part on events occurring on the cores, and a hybrid logic to combine the first power consumption level and a second power consumption level. Other embodiments are described and claimed.Type: GrantFiled: March 30, 2012Date of Patent: January 17, 2017Assignee: Intel CorporationInventors: Ankush Varma, Krishnakanth V. Sistla, Martin T. Rowland, Vivek Garg, James S. Burns
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Patent number: 9502082Abstract: Methods, apparatuses, and systems may provide a sensor to monitor a power consumption of a non-volatile random access memory (RAM) and a volatile RAM. A switch, connected to an output of the sensor, controls power to the non-volatile RAM, and a voltage regulator regulates a voltage of the non-volatile RAM and the volatile RAM. One or more memory slots receive the non-volatile RAM and the volatile RAM, and a processor receives information from the sensor, and controls the voltage regulator based on the received information. The voltage regulator comprises a plurality of registers to store power consumption information of the non-volatile RAM and the volatile RAM.Type: GrantFiled: June 24, 2015Date of Patent: November 22, 2016Assignee: Intel CorporationInventors: Thi Dang, James S. Burns, Russell J. Wunderlich, Jagannath Coimbatore Premkumar
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Publication number: 20160145987Abstract: A method of recovering hydrocarbons includes forming a first electrode by creating a first hydraulic fracture within the subsurface formation and pumping a first electrically conductive material into the first hydraulic fracture; forming a second electrode by creating a second hydraulic fracture within the subsurface formation and pumping a second electrically conductive material into the second hydraulic fracture; electrically connecting a first power transmitting mechanism to the first electrode; electrically connecting a second power transmitting mechanism to the second electrode; and heating the subsurface formation between the first electrode and the second electrode by transmitting an electrical current via the first power transmitting mechanism to the first electrode and via the second power transmitting mechanism to the second electrode and by flowing the electrical current from the first electrode to the second electrode.Type: ApplicationFiled: October 15, 2015Publication date: May 26, 2016Inventors: William A. Symington, Erik H. Clayton, Robert D. Kaminsky, Larry J. Manak, James S. Burns
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Patent number: 9335813Abstract: A method and system for dynamic or run-time reallocation of leakage current and dynamic power supply current of a processor. In one embodiment of the invention, the processor uses the variation in the leakage current of the processor to reduce the maximum current dissipation or power supply current of the processor (ICCmax). By reducing the maximum current dissipation, the system cost can be reduced as a less expensive power delivery system is required in one embodiment of the invention.Type: GrantFiled: May 28, 2013Date of Patent: May 10, 2016Assignee: Intel CorporationInventors: James S. Burns, Ashish V. Choubal, Arvind Raman, Johan G. Van De Groenendaal