Patents by Inventor Devon Bernard

Devon Bernard 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: 20210118552
    Abstract: A medical scan report labeling system is operable to transmit a medical report that includes natural language text to a first client device for display. Identified medical condition term data is received from the first client device in response. An alias mapping pair in a medical label alias database is identified by determining that a medical condition term of the alias mapping pair compares favorably to the identified medical condition term data. A medical code that corresponds to the alias mapping pair and a medical scan that corresponds to the medical report are transmitted to a second client device of an expert user for display, and accuracy data is received from the second client device in response. The medical code is mapped to the first medical scan in the medical scan database when the accuracy data indicates that the medical code compares favorably to the medical scan.
    Type: Application
    Filed: December 28, 2020
    Publication date: April 22, 2021
    Applicant: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Brian Basham, Rewon Child
  • Patent number: 10930387
    Abstract: A chest x-ray differential diagnosis system is operable to generate abnormality pattern data is generated for each of a received plurality of chest x-rays by identifying at least one pattern in each chest x-ray corresponding to an abnormality by utilizing a computer vision model that is trained on a plurality of training chest x-rays. Differential diagnosis data is generated for each chest x-ray based on the abnormality pattern data. Filtering parameters are received from a client device, and a filtered chest x-ray queue that includes a subset of chest x-rays is selected based on the filtering parameters and the differential diagnosis data is generated for transmission to the client device for display. Differential diagnosis data corresponding a chest x-ray indicated in chest x-ray selection data received from the client device is transmitted to the client device for display via the display device in conjunction with the chest x-ray.
    Type: Grant
    Filed: December 10, 2019
    Date of Patent: February 23, 2021
    Assignee: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Diogo Almeida, Ben Covington, Anthony Upton
  • Patent number: 10910097
    Abstract: A medical scan report labeling system is operable to transmit a medical report that includes natural language text to a first client device for display. Identified medical condition term data is received from the first client device in response. An alias mapping pair in a medical label alias database is identified by determining that a medical condition term of the alias mapping pair compares favorably to the identified medical condition term data. A medical code that corresponds to the alias mapping pair and a medical scan that corresponds to the medical report are transmitted to a second client device of an expert user for display, and accuracy data is received from the second client device in response. The medical code is mapped to the first medical scan in the medical scan database when the accuracy data indicates that the medical code compares favorably to the medical scan.
    Type: Grant
    Filed: August 15, 2017
    Date of Patent: February 2, 2021
    Assignee: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Brian Basham, Rewon Child
  • Patent number: 10896753
    Abstract: A lung screening assessment system is operable to receive a chest computed tomography (CT) scan that includes a plurality of cross sectional images. Nodule classification data of the chest CT scan is generated by utilizing a computer vision model that is trained on a plurality of training chest CT scans to identify a nodule in the plurality of cross sectional images and determine an assessment score. A lung screening report that includes the assessment score of the nodule classification data is generated for display on a display device associated with a user of the lung screening assessment system.
    Type: Grant
    Filed: December 10, 2019
    Date of Patent: January 19, 2021
    Assignee: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Ben Covington, Diogo Almeida, Brian Basham, Jeremy Howard, Anthony Upton, John Zedlewski
  • Publication number: 20200386598
    Abstract: A computing system having a memory and a processor configured to process flow data packets (FDPs) collected from a set of sensor devices, each installed in a toilet that collects a flow data packet (FDP) in response to a detected event, wherein each FDP includes a sequence of flow rate values collected over the course of the detected event. The processor is configured to: issue a first type of alert in response to a number of flow rate values in a current FDP being above a threshold; issue a second type of alert in response to a detected abnormal behavior of the current FDP relative to previously collected FDPs for an associated toilet; and issue a third type of alert based on a water usage for the toilet, wherein the water usage is based on calculated flow rate for a toilet determined from at least one FDP.
    Type: Application
    Filed: June 5, 2020
    Publication date: December 10, 2020
    Inventors: Karl Appel, Matthew Cusack, Frank Lipowitz, John Gebbia, Trey Alexander Briccetti, Devon Bernard
  • Publication number: 20200381105
    Abstract: A medical scan diagnosing system is operable to receive a medical scan. Diagnosis data of the medical scan is generated by performing a medical scan inference function on the medical scan. The first medical scan is transmitted to a first client device associated with a user of the medical scan diagnosing system in response to the diagnosis data indicating that the medical scan corresponds to a non-normal diagnosis. The medical scan is displayed to the user via an interactive interface displayed by a display device corresponding to the first client device. Review data is received from the first client device, where the review data is generated by the first client device in response to a prompt via the interactive interface. Updated diagnosis data is generated based on the review data. The updated diagnosis data is transmitted to a second client device associated with a requesting entity.
    Type: Application
    Filed: August 20, 2020
    Publication date: December 3, 2020
    Applicant: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Alan Liu
  • Patent number: 10811134
    Abstract: A medical scan diagnosing system is operable to receive a medical scan. Diagnosis data of the medical scan is generated by performing a medical scan inference function on the medical scan. The first medical scan is transmitted to a first client device associated with a user of the medical scan diagnosing system in response to the diagnosis data indicating that the medical scan corresponds to a non-normal diagnosis. The medical scan is displayed to the user via an interactive interface displayed by a display device corresponding to the first client device. Review data is received from the first client device, where the review data is generated by the first client device in response to a prompt via the interactive interface. Updated diagnosis data is generated based on the review data. The updated diagnosis data is transmitted to a second client device associated with a requesting entity.
    Type: Grant
    Filed: August 22, 2017
    Date of Patent: October 20, 2020
    Assignee: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Alan Liu
  • Patent number: 10755811
    Abstract: A medical scan comparison system is operable to receive a medical scan via a network and to generate similar scan data. The similar scan data includes a subset of medical scans from a medical scan database and is generated by performing an abnormality similarity function to determine that a set of abnormalities included in the subset of medical scans compare favorably to an abnormality identified in the medical scan. At least one cross-sectional image is selected from each medical scan of the subset of medical scans for display on a display device associated with a user of the medical scan comparison system in conjunction with the medical scan.
    Type: Grant
    Filed: May 23, 2019
    Date of Patent: August 25, 2020
    Assignee: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Anthony Upton, Ben Covington, Jeremy Howard
  • Patent number: 10748652
    Abstract: A medical scan image analysis system is operable to receive a plurality of medical scans that represent a three-dimensional anatomical region and include a plurality of cross-sectional image slices. A plurality of three-dimensional subregions corresponding to each of the plurality of medical scans are generated by selecting a proper subset of the plurality of cross-sectional image slices from each medical scan, and by further selecting a two-dimensional subregion from each proper subset of cross-sectional image slices. A learning algorithm is performed on the plurality of three-dimensional subregions to generate a fully convolutional neural network. Inference data corresponding to a new medical scan received via the network is generated by performing an inference algorithm on the new medical scan by utilizing the fully convolutional neural network. An inferred abnormality is identified in the new medical scan based on the inference data.
    Type: Grant
    Filed: May 23, 2019
    Date of Patent: August 18, 2020
    Assignee: Enlitic, Inc.
    Inventors: Li Yao, Devon Bernard, Kevin Lyman, Diogo Almeida, Jeremy Howard
  • Publication number: 20200118670
    Abstract: A medical scan annotator system is operable to select a medical scan for transmission via a network to a first client device and a second client device for display via an interactive interface, and annotation data is received from the first client device and the second client device in response. Annotation similarity data is generated by comparing the first annotation data to the second annotation data, and consensus annotation data is generated based on the first annotation data and the second annotation data in response to the annotation similarity data indicating that the difference between the first annotation data and the second annotation data compares favorably to an annotation discrepancy threshold. The consensus annotation data is mapped to the medical scan in a medical scan database.
    Type: Application
    Filed: December 11, 2019
    Publication date: April 16, 2020
    Applicant: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Brian Basham, Ben Covington
  • Publication number: 20200111561
    Abstract: A lung screening assessment system is operable to receive a chest computed tomography (CT) scan that includes a plurality of cross sectional images. Nodule classification data of the chest CT scan is generated by utilizing a computer vision model that is trained on a plurality of training chest CT scans to identify a nodule in the plurality of cross sectional images and determine an assessment score. A lung screening report that includes the assessment score of the nodule classification data is generated for display on a display device associated with a user of the lung screening assessment system.
    Type: Application
    Filed: December 10, 2019
    Publication date: April 9, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Ben Covington, Diogo Almeida, Brian Basham, Jeremy Howard, Anthony Upton, John Zedlewski
  • Publication number: 20200111562
    Abstract: A chest x-ray differential diagnosis system is operable to generate abnormality pattern data is generated for each of a received plurality of chest x-rays by identifying at least one pattern in each chest x-ray corresponding to an abnormality by utilizing a computer vision model that is trained on a plurality of training chest x-rays. Differential diagnosis data is generated for each chest x-ray based on the abnormality pattern data. Filtering parameters are received from a client device, and a filtered chest x-ray queue that includes a subset of chest x-rays is selected based on the filtering parameters and the differential diagnosis data is generated for transmission to the client device for display. Differential diagnosis data corresponding a chest x-ray indicated in chest x-ray selection data received from the client device is transmitted to the client device for display via the display device in conjunction with the chest x-ray.
    Type: Application
    Filed: December 10, 2019
    Publication date: April 9, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Diogo Almeida, Ben Covington, Anthony Upton
  • Patent number: 10553311
    Abstract: A lung screening assessment system is operable to receive a chest computed tomography (CT) scan that includes a plurality of cross sectional images. Nodule classification data of the chest CT scan is generated by utilizing a computer vision model that is trained on a plurality of training chest CT scans to identify a nodule in the plurality of cross sectional images and determine an assessment score. A lung screening report that includes the assessment score of the nodule classification data is generated for display on a display device associated with a user of the lung screening assessment system.
    Type: Grant
    Filed: August 30, 2017
    Date of Patent: February 4, 2020
    Assignee: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Ben Covington, Diogo Almeida, Brian Basham, Jeremy Howard, Anthony Upton, John Zedlewski
  • Patent number: 10553312
    Abstract: A medical scan annotator system is operable to select a medical scan for transmission via a network to a first client device and a second client device for display via an interactive interface, and annotation data is received from the first client device and the second client device in response. Annotation similarity data is generated by comparing the first annotation data to the second annotation data, and consensus annotation data is generated based on the first annotation data and the second annotation data in response to the annotation similarity data indicating that the difference between the first annotation data and the second annotation data compares favorably to an annotation discrepancy threshold. The consensus annotation data is mapped to the medical scan in a medical scan database.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: February 4, 2020
    Assignee: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Brian Basham, Ben Covington
  • Patent number: 10541050
    Abstract: A chest x-ray differential diagnosis system is operable to generate abnormality pattern data is generated for each of a received plurality of chest x-rays by identifying at least one pattern in each chest x-ray corresponding to an abnormality by utilizing a computer vision model that is trained on a plurality of training chest x-rays. Differential diagnosis data is generated for each chest x-ray based on the abnormality pattern data. Filtering parameters are received from a client device, and a filtered chest x-ray queue that includes a subset of chest x-rays is selected based on the filtering parameters and the differential diagnosis data is generated for transmission to the client device for display. Differential diagnosis data corresponding a chest x-ray indicated in chest x-ray selection data received from the client device is transmitted to the client device for display via the display device in conjunction with the chest x-ray.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: January 21, 2020
    Assignee: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Diogo Almeida, Ben Covington, Anthony Upton
  • Publication number: 20190279760
    Abstract: A medical scan image analysis system is operable to receive a plurality of medical scans that represent a three-dimensional anatomical region and include a plurality of cross-sectional image slices. A plurality of three-dimensional subregions corresponding to each of the plurality of medical scans are generated by selecting a proper subset of the plurality of cross-sectional image slices from each medical scan, and by further selecting a two-dimensional subregion from each proper subset of cross-sectional image slices. A learning algorithm is performed on the plurality of three-dimensional subregions to generate a fully convolutional neural network. Inference data corresponding to a new medical scan received via the network is generated by performing an inference algorithm on the new medical scan by utilizing the fully convolutional neural network. An inferred abnormality is identified in the new medical scan based on the inference data.
    Type: Application
    Filed: May 23, 2019
    Publication date: September 12, 2019
    Applicant: Enlitic, Inc.
    Inventors: Li Yao, Devon Bernard, Kevin Lyman, Diogo Almeida, Jeremy Howard
  • Publication number: 20190279761
    Abstract: A medical scan comparison system is operable to receive a medical scan via a network and to generate similar scan data. The similar scan data includes a subset of medical scans from a medical scan database and is generated by performing an abnormality similarity function to determine that a set of abnormalities included in the subset of medical scans compare favorably to an abnormality identified in the medical scan. At least one cross-sectional image is selected from each medical scan of the subset of medical scans for display on a display device associated with a user of the medical scan comparison system in conjunction with the medical scan.
    Type: Application
    Filed: May 23, 2019
    Publication date: September 12, 2019
    Applicant: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Anthony Upton, Ben Covington, Jeremy Howard
  • Patent number: 10360999
    Abstract: A medical scan comparison system is operable to receive a medical scan via a network and to generate similar scan data. The similar scan data includes a subset of medical scans from a medical scan database and is generated by performing an abnormality similarity function to determine that a set of abnormalities included in the subset of medical scans compare favorably to an abnormality identified in the medical scan. At least one cross-sectional image is selected from each medical scan of the subset of medical scans for display on a display device associated with a user of the medical scan comparison system in conjunction with the medical scan.
    Type: Grant
    Filed: August 30, 2017
    Date of Patent: July 23, 2019
    Assignee: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Anthony Upton, Ben Covington, Jeremy Howard
  • Patent number: 10340044
    Abstract: A medical scan image analysis system is operable to receive a plurality of medical scans that represent a three-dimensional anatomical region and include a plurality of cross-sectional image slices. A plurality of three-dimensional subregions corresponding to each of the plurality of medical scans are generated by selecting a proper subset of the plurality of cross-sectional image slices from each medical scan, and by further selecting a two-dimensional subregion from each proper subset of cross-sectional image slices. A learning algorithm is performed on the plurality of three-dimensional subregions to generate a fully convolutional neural network. Inference data corresponding to a new medical scan received via the network is generated by performing an inference algorithm on the new medical scan by utilizing the fully convolutional neural network. An inferred abnormality is identified in the new medical scan based on the inference data.
    Type: Grant
    Filed: August 30, 2017
    Date of Patent: July 2, 2019
    Assignee: Enlitic, Inc.
    Inventors: Li Yao, Devon Bernard, Kevin Lyman, Diogo Almeida, Jeremy Howard
  • Publication number: 20190066835
    Abstract: A chest x-ray differential diagnosis system is operable to generate abnormality pattern data is generated for each of a received plurality of chest x-rays by identifying at least one pattern in each chest x-ray corresponding to an abnormality by utilizing a computer vision model that is trained on a plurality of training chest x-rays. Differential diagnosis data is generated for each chest x-ray based on the abnormality pattern data. Filtering parameters are received from a client device, and a filtered chest x-ray queue that includes a subset of chest x-rays is selected based on the filtering parameters and the differential diagnosis data is generated for transmission to the client device for display. Differential diagnosis data corresponding a chest x-ray indicated in chest x-ray selection data received from the client device is transmitted to the client device for display via the display device in conjunction with the chest x-ray.
    Type: Application
    Filed: October 24, 2018
    Publication date: February 28, 2019
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Diogo Almeida, Ben Covington, Anthony Upton