Patents by Inventor Olya Stringfield

Olya Stringfield 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).

  • ARTIFICIAL INTELLIGENCE-BASED METHODS FOR GRADING, SEGMENTING, AND/OR ANALYZING LUNG ADENOCARCINOMA PATHOLOGY SLIDES
    Publication number: 20250022128
    Abstract: An example method for grading, segmenting, and analyzing lung adenocarcinoma (LUAD) pathology slides using artificial intelligence is described herein. The method includes receiving a digital pathology image of a LUAD tissue sample; inputting the digital pathology image into an artificial intelligence model; and grading, using the artificial intelligence model, the one or more tumors within the LUAD tissue sample.
    Type: Application
    Filed: November 23, 2022
    Publication date: January 16, 2025
    Inventors: Elsa FLORES, John LOCKHART, Olya STRINGFIELD, Mahmoud ABDALAH
  • Radiologically identified tumor habitats
    Patent number: 10827945
    Abstract: Virtually every cancer patient is imaged with CT, PET or MRI. Importantly, such imaging reveals that tumors are complex and heterogeneous, often containing multiple habitats within them. Disclosed herein are methods for analyzing these images to infer cellular and molecular structure in each of these habitats. The methods can involve spatially superimposing two or more radiological images of the tumor sufficient to define regional habitat variations in two or more ecological dynamics in the tumor, and comparing the habitat variations to one or more controls to predict the severity of the tumor.
    Type: Grant
    Filed: March 10, 2015
    Date of Patent: November 10, 2020
    Assignees: H. LEE. MOFFITT CANCER CENTER AND RESEARCH INSTITUTE, INC., UNIVERSITY OF SOUTH FLORIDA
    Inventors: Robert J. Gillies, Robert A. Gatenby, Natarajan Raghunand, John Arrington, Olya Stringfield, Yoganand Balagurunathan, Dmitry B. Goldgof, Lawrence O. Hall
  • Quantitative predictors of tumor severity
    Patent number: 10339648
    Abstract: Disclosed are methods for quantitatively predicting the severity of a tumor in a subject. In some embodiments, the methods further comprise selecting a course of therapy for the subject. In some embodiments, the tumor comprises is non-small cell lung cancer.
    Type: Grant
    Filed: January 21, 2014
    Date of Patent: July 2, 2019
    Assignee: H. LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE, INC.
    Inventors: Olya Stringfield, Robert J. Gillies
  • RADIOLOGICALLY IDENTIFIED TUMOR HABITATS
    Publication number: 20170071496
    Abstract: Virtually every cancer patient is imaged with CT, PET or MRI. Importantly, such imaging reveals that tumors are complex and heterogeneous, often containing multiple habitats within them. Disclosed herein are methods for analyzing these images to infer cellular and molecular structure in each of these habitats. The methods can involve spatially superimposing two or more radiological images of the tumor sufficient to define regional habitat variations in two or more ecological dynamics in the tumor, and comparing the habitat variations to one or more controls to predict the severity of the tumor.
    Type: Application
    Filed: March 10, 2015
    Publication date: March 16, 2017
    Inventors: Robert J. Gillies, Robert A. Gatenby, Natarajan Raghunand, John Arrington, Olya Stringfield, Yoganand Balagurunathan, Dmitry B. Goldgof, Lawrence O. Hall