Patents by Inventor W. Louis Cleveland

W. Louis Cleveland 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).

  • Patent number: 9504665
    Abstract: The present invention provides for a method of treating OCD or an Obsessive-Compulsive Spectrum Disorder (OCSD), such as BDD or ADHD, using a high-dose glycine treatment.
    Type: Grant
    Filed: September 10, 2013
    Date of Patent: November 29, 2016
    Inventor: W. Louis Cleveland
  • Patent number: 9415030
    Abstract: The present invention provides for a method of treating OCD or an Obsessive-Compulsive Spectrum Disorder (OCSD), such as BDD or ADHD, using a high-dose glycine treatment.
    Type: Grant
    Filed: May 6, 2013
    Date of Patent: August 16, 2016
    Inventor: W. Louis Cleveland
  • Publication number: 20140011878
    Abstract: The present invention provides for a method of treating OCD or an Obsessive-Compulsive Spectrum Disorder (OCSD), such as BDD or ADHD, using a high-dose glycine treatment.
    Type: Application
    Filed: September 10, 2013
    Publication date: January 9, 2014
    Inventor: W. Louis Cleveland
  • Patent number: 8604080
    Abstract: The present invention provides for a method of treating OCD or an Obsessive-Compulsive Spectrum Disorder (OCSD), such as BDD or ADHD, using a high-dose glycine treatment.
    Type: Grant
    Filed: February 4, 2008
    Date of Patent: December 10, 2013
    Inventor: W. Louis Cleveland
  • Publication number: 20130251635
    Abstract: The present invention provides for a method of treating OCD or an Obsessive-Compulsive Spectrum Disorder (OCSD), such as BDD or ADHD, using a high-dose glycine treatment.
    Type: Application
    Filed: May 6, 2013
    Publication date: September 26, 2013
    Inventor: W. Louis Cleveland
  • Patent number: 7958063
    Abstract: A method of identifying and localizing objects belonging to one of three or more classes, includes deriving vectors, each being mapped to one of the objects, where each of the vectors is an element of an N-dimensional space. The method includes training an ensemble of binary classifiers with a CISS technique, using an ECOC technique. For each object corresponding to a class, the method includes calculating a probability that the associated vector belongs to a particular class, using an ECOC probability estimation technique. In another embodiment, increased detection accuracy is achieved by using images obtained with different contrast methods. A nonlinear dimensional reduction technique, Kernel PCA, was employed to extract features from the multi-contrast composite image. The Kernel PCA preprocessing shows improvements over traditional linear PCA preprocessing possibly due to its ability to capture high-order, nonlinear correlations in the high dimensional image space.
    Type: Grant
    Filed: April 25, 2007
    Date of Patent: June 7, 2011
    Assignee: Trustees of Columbia University in the City of New York
    Inventors: Xi Long, W. Louis Cleveland, Y. Lawrence Yao
  • Publication number: 20100113598
    Abstract: The present invention provides for a method of treating OCD or an Obsessive-Compulsive Spectrum Disorder (OCSD), such as BDD or ADHD, using a high-dose glycine treatment.
    Type: Application
    Filed: February 4, 2008
    Publication date: May 6, 2010
    Applicant: THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF
    Inventor: W. Louis Cleveland
  • Publication number: 20080082468
    Abstract: A method of identifying and localizing objects belonging to one of three or more classes, includes deriving vectors, each being mapped to one of the objects, where each of the vectors is an element of an N-dimensional space. The method includes training an ensemble of binary classifiers with a CISS technique, using an ECOC technique. For each object corresponding to a class, the method includes calculating a probability that the associated vector belongs to a particular class, using an ECOC probability estimation technique. In another embodiment, increased detection accuracy is achieved by using images obtained with different contrast methods. A nonlinear dimensional reduction technique, Kernel PCA, was employed to extract features from the multi-contrast composite image. The Kernel PCA preprocessing shows improvements over traditional linear PCA preprocessing possibly due to its ability to capture high-order, nonlinear correlations in the high dimensional image space.
    Type: Application
    Filed: April 25, 2007
    Publication date: April 3, 2008
    Applicant: The Trustees of Columbia University in the City of New York
    Inventors: Xi Long, W. Louis Cleveland, Y. Yao