Patents by Inventor Rohit Pardasani

Rohit Pardasani 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: 20240335171
    Abstract: A waveform processing system including a patient monitor, a display device, and a processor configured to control the display device to display a location in a stream of waveform data of a segment including a specified event such as aberration or variation in the waveform data, wherein the location of the segment is identified based on aggregating outputs of an AI model performing sliding window inferences on the stream of waveform data. Performing the sliding window inferences on the stream of waveform data may include dividing the waveform data into a plurality of overlapping chunks, each chunk comprising consecutive data values extracted from the stream of waveform data over a specified duration, and inputting each chunk into the AI model to generate arrays of output values indicating a presence or absence the segment, which may then be aggregated.
    Type: Application
    Filed: April 4, 2023
    Publication date: October 10, 2024
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan, Renee L Vitullo, Merrinda Janas
  • Patent number: 12106838
    Abstract: Methods and systems are provided for generating respiratory support recommendations. In one embodiment, a method includes extracting imaging features from patient imaging information for a patient, extracting non-imaging features from patient clinical data of the patient, entering the imaging features and the non-imaging features to a joint model trained to output respiratory support recommendations as a function of the imaging features and the non-imaging features, and displaying one or more respiratory support recommendations output by the joint model.
    Type: Grant
    Filed: June 29, 2021
    Date of Patent: October 1, 2024
    Assignee: GE PRECISION HEALTHCARE LLC
    Inventors: Hariharan Ravishankar, Abhijit Patil, Rohit Pardasani
  • Patent number: 12094611
    Abstract: Techniques are described for performing fetal heart rate (FHR) analytics using machine learning techniques. According to an embodiment, computer-implemented method comprises training a machine learning model using a supervised machine learning process to identify patterns in training cardiotocograph data that correspond to defined physiological events associated with respective fetuses and mothers of the fetuses represented in the training cardiotocograph data. The method further comprises receiving new cardiotocograph data for a fetus and mother in real-time over a period of labor and applying the machine learning model to the new cardiotocograph data as it is received to identify the patterns in the new cardiotocograph data.
    Type: Grant
    Filed: November 2, 2021
    Date of Patent: September 17, 2024
    Assignee: GE Precision Healthcare LLC
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan, Renee L Vitullo
  • Publication number: 20240282451
    Abstract: One or more systems, devices, computer-implemented methods and/or computer program products of use provided herein relate to artificial intelligence (AI) to generate labor and delivery-based predictions. A system can comprise a processor that can execute computer-executable components stored in memory, wherein the computer-executable components can comprise a first AI model that can generate first data comprising one or more labor and delivery predictions applicable to one or more fetuses and a mother of the one or more fetuses, during labor, by analyzing second data comprising cardiotocography (CTG) analysis data of the one or more fetuses and the mother generated by a second AI model and third data comprising maternal health analysis data of the mother generated by a third AI model, wherein the first AI model can be a multistage AI model comprising respective models directed to predicting respective ones of the one or more labor and delivery predictions.
    Type: Application
    Filed: April 10, 2024
    Publication date: August 22, 2024
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan
  • Patent number: 11941806
    Abstract: Automated assessment for a fetus may be applied based on imaging data obtained during medical imaging examination of the fetus, with the applying including processing imaging data corresponding to a plurality of a cross-section imaging slices corresponding to a limb of the fetus, where the processing includes for each imaging slice: automatically generating a predicted outer mask for an outer contour of the limb based on application of a first pre-trained model to imaging data corresponding to the imaging slice; and automatically generating a segmentation of fat-lean mask for the imaging slice based on application of a second pre-trained model to both of the imaging data corresponding to the imaging slice and the generated predicted output mask; and applying based on the processing of the imaging data corresponding to the plurality of a cross-section imaging slices: a fractional limb volume assessment; and a fat-lean mass assessment.
    Type: Grant
    Filed: September 17, 2021
    Date of Patent: March 26, 2024
    Assignee: GE Precision Healthcare LLC
    Inventors: Rohit Pardasani, Hrithik Auchar
  • Publication number: 20230136298
    Abstract: Techniques are described for performing fetal heart rate (FHR) analytics using machine learning techniques. According to an embodiment, computer-implemented method comprises training a machine learning model using a supervised machine learning process to identify patterns in training cardiotocograph data that correspond to defined physiological events associated with respective fetuses and mothers of the fetuses represented in the training cardiotocograph data. The method further comprises receiving new cardiotocograph data for a fetus and mother in real-time over a period of labor and applying the machine learning model to the new cardiotocograph data as it is received to identify the patterns in the new cardiotocograph data.
    Type: Application
    Filed: November 2, 2021
    Publication date: May 4, 2023
    Inventors: Rohit Pardasani, Siddharth Ajith, John Michael Jordan, Renee L Vitullo
  • Publication number: 20230087363
    Abstract: Automated assessment for a fetus may be applied based on imaging data obtained during medical imaging examination of the fetus, with the applying including processing imaging data corresponding to a plurality of a cross-section imaging slices corresponding to a limb of the fetus, where the processing includes for each imaging slice: automatically generating a predicted outer mask for an outer contour of the limb based on application of a first pre-trained model to imaging data corresponding to the imaging slice; and automatically generating a segmentation of fat-lean mask for the imaging slice based on application of a second pre-trained model to both of the imaging data corresponding to the imaging slice and the generated predicted output mask; and applying based on the processing of the imaging data corresponding to the plurality of a cross-section imaging slices: a fractional limb volume assessment; and a fat-lean mass assessment.
    Type: Application
    Filed: September 17, 2021
    Publication date: March 23, 2023
    Inventors: Rohit Pardasani, Hrithik Auchar
  • Publication number: 20230031328
    Abstract: Systems and techniques for monitoring, predicting and/or alerting for short-term oxygen support needs of patients are presented. A system can include a data collection component that receives multimodal patient data for a patient having a respiratory condition in association with monitoring and treating the respiratory condition in real-time, the multimodal patient data comprising at least physiological data regarding physiological parameters tracked for the patient over a period of time, and current oxygen support data regarding a current oxygen support mechanism of the patient.
    Type: Application
    Filed: December 22, 2021
    Publication date: February 2, 2023
    Inventors: Hariharan Ravishankar, Abhijit Patil, Rohit Pardasani, Dirk Johannes Varelmann, Pankaj Sarin, Marcio Aloisio Bezerra Cavalcanti Rockenbach, Quanzheng Li
  • Publication number: 20210407648
    Abstract: Methods and systems are provided for generating respiratory support recommendations. In one embodiment, a method includes extracting imaging features from patient imaging information for a patient, extracting non-imaging features from patient clinical data of the patient, entering the imaging features and the non-imaging features to a joint model trained to output respiratory support recommendations as a function of the imaging features and the non-imaging features, and displaying one or more respiratory support recommendations output by the joint model.
    Type: Application
    Filed: June 29, 2021
    Publication date: December 30, 2021
    Inventors: Hariharan Ravishankar, Abhijit Patil, Rohit Pardasani
  • Publication number: 20200178903
    Abstract: A method of monitoring a patient with respect to a particular medical condition includes providing a machine learning model trained to assign a weight to each of a predefined set of features so as to calculate a risk severity index of a particular medical condition. A long time interval of time-synchronized parameter data is received for each of at least two physiological parameters, and the long time interval is divided into multiple segments each containing a predefined time increment of the parameter data. A set of feature values are determined for the segment based on the parameter data therein, including a feature value for each of the predefined set of features related to the particular medical condition. With the trained machine learning model, assigning a weight to each of the predefined set of features, and then a risk severity index of the particular medical condition is calculated for the long time interval based on the set of feature values.
    Type: Application
    Filed: December 10, 2018
    Publication date: June 11, 2020
    Applicant: General Electric Company
    Inventors: Rupanjali Chaudhuri, Rohit Pardasani, Hariharan Ravishankar, Guy Vesto