Patents by Inventor Eric Elster

Eric Elster 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: 20200335179
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of the healing rate of an acute traumatic wound is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of the healing rate of an acute traumatic wound.
    Type: Application
    Filed: July 7, 2020
    Publication date: October 22, 2020
    Inventors: Alexander Stojadinovic, Eric A. Elster, Doug K. Tadaki, John S. Eberhardt, III, Trevor Brown, Thomas A. Davis, Jonathan Forsberg, Jason Hawksworth
  • Patent number: 10726943
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of the healing rate of an acute traumatic wound is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of the healing rate of an acute traumatic wound.
    Type: Grant
    Filed: April 8, 2011
    Date of Patent: July 28, 2020
    Assignees: THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY, THE GOVERNMENT OF THE UNITED STATES, AS REPRESENTED BY THE SECRETARY OF THE ARMY, DECISIONQ CORPORATION
    Inventors: Alexander Stojadinovic, Eric Elster, Doug K. Tadaki, John S. Eberhardt, III, Trevor Brown, Thomas A. Davis, Jonathan Forsberg, Jason Hawksworth
  • Publication number: 20190355473
    Abstract: Described herein are systems and methods for determining if a subject has an increased risk of having or developing pneumonia or symptoms associated with pneumonia. Also described are systems and methods for predicting a pneumonia outcome for a subject, systems and methods for generating a model for predicting a pneumonia outcome in a subject, systems and method for determining a subject's risk profile for pneumonia, method of determining that a subject has an increased risk of developing pneumonia, and methods of treating a subject determined to have an elevated risk of developing pneumonia, methods of detecting panels of biomarkers in a subject, and methods of assessing risk factors in a subject having an injury, as well as related devices and kits.
    Type: Application
    Filed: January 5, 2018
    Publication date: November 21, 2019
    Applicant: Henry M. Jackson Foundation for the Advancement of Military Medicine
    Inventors: Seth A. Schobel, Eric A. Elster, Beverly J. Gaucher
  • Publication number: 20190354814
    Abstract: Described herein are systems and methods for determining if a subject has an increased risk of having or developing bacteremia or symptoms associated with bacteremia. Also described are systems and methods for predicting a bacteremia outcome for a subject, systems and methods for generating a model for predicting a bacteremia outcome in a subject, systems and method for determining a subject's risk profile for bacteremia, method of determining that a subject has an increased risk of developing bacteremia, and methods of treating a subject determined to have an elevated risk of developing bacteremia, methods of detecting panels of biomarkers in a subject, and methods of assessing risk factors in a subject having an injury, as well as related devices and kits.
    Type: Application
    Filed: January 5, 2018
    Publication date: November 21, 2019
    Applicant: Henry M. Jackson Foundation for the Advancement of Military Medicine
    Inventors: Seth A. Schobel, Eric A. Elster, Beverly J. Gaucher
  • Patent number: 9561006
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
    Type: Grant
    Filed: October 27, 2012
    Date of Patent: February 7, 2017
    Assignee: The United States of America as represented by the Secretary of the Navy
    Inventors: Eric A. Elster, Doug Tadaki, Trevor S. Brown, Rahul Jindal
  • Publication number: 20160353994
    Abstract: A method for detecting and monitoring the progression of heterotopic ossification by Raman spectral analysis. Analysis of heterotopic ossification progress can be conducted using invasive or invasive means using specific Raman spectroscopy. Analysis is by determination of a number of Raman spectral parameters including the area under one or more of the vibrational bands, band area ratios, band height, ratios of band heights and shift in band center.
    Type: Application
    Filed: January 2, 2014
    Publication date: December 8, 2016
    Inventors: Nicole Crane, Eric A. Elster, Jonathan Forsberg, Douglas Tadaki
  • Patent number: 9457052
    Abstract: A method inducing chimerism and allograft tolerance by co-infusion of stem/progenitor-like cells and donor cells, wherein the donor cells can be bone marrow cells. The method also comprises the conditioning comprising depletion of CD4+ and CD8+ T-cells and administration of low doses of anti-neoplastic drugs. The inventive method comprises an aspect wherein allograft tolerance is induced without systemically suppressing the immune system.
    Type: Grant
    Filed: March 14, 2014
    Date of Patent: October 4, 2016
    Assignee: The United States of America as Represented by the Secretary of the Navy
    Inventors: Thomas A. Davis, Khairul Anam, Eric A. Elster, Douglas K. Tadaki
  • Publication number: 20160256489
    Abstract: A method inducing chimerism and allograft tolerance by co-infusion of stein/progenitor-like cells and donor cells, wherein the donor cells can be bone marrow cells. The method also comprises the conditioning comprising depletion of CD4+ and CD8+ T-cells and administration of low doses of anti-neoplastic drugs. The inventive method comprises an aspect wherein allograft tolerance is induced without systemically suppressing the immune system.
    Type: Application
    Filed: March 14, 2014
    Publication date: September 8, 2016
    Inventors: Thomas A. Davis, Khairul Anam, Eric A. Elster, Douglas K. Tadaki
  • Publication number: 20160206249
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
    Type: Application
    Filed: October 27, 2012
    Publication date: July 21, 2016
    Inventors: Eric A. Elster, Doug Tadaki, Trevor S. Brown, Rahul Jindal
  • Publication number: 20150258144
    Abstract: A method inducing chimerism and allograft tolerance by co-infusion of stein/progenitor-like cells and donor cells, wherein the donor cells can be bone marrow cells. The method also comprises the conditioning comprising depletion of CD4+ and CD8+ T-cells and administration of low doses of anti-neoplastic drugs. The inventive method comprises an aspect wherein allograft tolerance is induced without systemically suppressing the immune system.
    Type: Application
    Filed: March 14, 2014
    Publication date: September 17, 2015
    Inventors: Thomas A. Davis, Khairul Anam, Eric A. Elster, Douglas K. Tadaki
  • Publication number: 20150182119
    Abstract: A method for detecting and monitoring the progression of heterotopic ossification by Raman spectral analysis. Analysis of heterotopic ossification progress can be conducted using invasive or invasive means using specific Raman spectroscopy. Analysis is by determination of a number of Raman spectral parameters including the area under one or more of the vibrational bands, band area ratios, band height, ratios of band heights and shift in band center.
    Type: Application
    Filed: January 2, 2014
    Publication date: July 2, 2015
    Inventors: Nicole Crane, Eric A. Elster, Jonathan Forsberg, Douglas Tadaki
  • Publication number: 20140122382
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
    Type: Application
    Filed: October 27, 2012
    Publication date: May 1, 2014
    Inventors: Eric A. Elster, Doug Tadaki, Trevor S. Brown, Rahul Jindal
  • Patent number: 8510245
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of transplant glomerulopathy. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of transplant glomerulopathy is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant glomerulopathy.
    Type: Grant
    Filed: April 8, 2011
    Date of Patent: August 13, 2013
    Assignee: The United States of America as Represented by the Secretary of the Army
    Inventors: Alexander Stojadinovic, Eric A. Elster, Doug K. Tadaki, John S. Eberhardt, III, Trevor Brown, Thomas A. Davis, Jonathan Forsberg, Jason Hawksworth, Roslyn Mannon
  • Publication number: 20120076776
    Abstract: A method for preventing inflammation, comprising administering to a subject a lymphocyte sequestrating or depletion agent before the onset of inflammation. A method for treating inflammation caused by an injury or an infection, comprising depleting immune lymphocyte of a subject by administering to said subject a lymphocyte sequestrating or depletion agent during or after said event. A method for preventing or treating abdominal adhesion comprising administering to a subject a lymphocyte sequestering or a lymphocyte depletion agent.
    Type: Application
    Filed: February 4, 2011
    Publication date: March 29, 2012
    Inventors: ERIC ELSTER, DOUG TADAKI, JASON HAWKSWORTH, THOMAS DAVIS
  • Publication number: 20110295782
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of disease.
    Type: Application
    Filed: October 15, 2009
    Publication date: December 1, 2011
    Inventors: Alexander Stojadinovic, Eric A. Elster, Doug K. Tadaki, John S. Eberhardt, III, Trevor S. Brown, Thomas A. Davis, Jonathan Forsberg, Jason Hawksworth, Roslyn Mannon, Aviram Nissan
  • Publication number: 20110289035
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of disease. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of the healing rate of an acute traumatic wound is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of the healing rate of an acute traumatic wound.
    Type: Application
    Filed: April 8, 2011
    Publication date: November 24, 2011
    Inventors: Alexander Stojadinovic, Eric Elster, Doug K. Tadaki, John S. Eberhardt, III, Trevor Brown, Thomas A. Davis, Jonathan Forsberg, Jason Hawksworth
  • Publication number: 20110289036
    Abstract: An embodiment of the invention provides a method for determining a patient-specific probability of transplant glomerulopathy. The method collects clinical parameters from a plurality of patients to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of transplant glomerulopathy is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative planning. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant glomerulopathy.
    Type: Application
    Filed: April 8, 2011
    Publication date: November 24, 2011
    Inventors: Alexander Stojadinovic, Eric A. Elster, Doug K. Tadaki, John S. Eberhardt, III, Trevor Brown, Thomas A. Davis, Jonathan Forsberg, Jason Hawksworth, Roslyn Mannon
  • Publication number: 20100182415
    Abstract: A system and method for real-time or near real-time monitoring of tissue/organ oxygenation through visual assessment of contrast enhanced images of the target area of tissue or organ. Video of a target tissue/organ was acquired during surgery, selected image frames were extracted. Each extracted image is separated into red, green and blue CCD responses. A modified contrast image was created by subtracting blue CCD responses from red CCD responses, and plotting the resultant image using a modified colormap. Overlaying said modified contrast image onto the original extracted image frame under a selected transparency range, and display it for review.
    Type: Application
    Filed: December 9, 2009
    Publication date: July 22, 2010
    Inventors: Eric A. Elster, Doug K. Tadaki, Nicole J. Crane, Scott W. Huffman, Ira W. Levin