Patents by Inventor Benjamin S. Glicksberg

Benjamin S. Glicksberg 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).

  • Surfacing insights into left and right ventricular dysfunction through deep learning
    Patent number: 12102485
    Abstract: Introduced here approaches to developing, training, and implementing algorithms to cardiac dysfunction through automated analysis of physiological data. As an example, a model may be developed and then trained to quantify left and right ventricular dysfunction using electrocardiogram waveform data that is associated with a population of individuals who are diverse in terms of age, gender, ethnicity, socioeconomic status, and the like. This approach to training allows the model to predict the presence of left and right ventricular dysfunction in a diverse population. Also introduced here is a regression framework for predicting numeric values of left ventricular ejection fraction.
    Type: Grant
    Filed: April 5, 2022
    Date of Patent: October 1, 2024
    Assignee: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
    Inventors: Akhil Vaid, Girish N. Nadkarni, Benjamin S. Glicksberg
  • SURFACING INSIGHTS INTO LEFT AND RIGHT VENTRICULAR DYSFUNCTION THROUGH DEEP LEARNING
    Publication number: 20230309967
    Abstract: Introduced here approaches to developing, training, and implementing algorithms to cardiac dysfunction through automated analysis of physiological data. As an example, a model may be developed and then trained to quantify left and right ventricular dysfunction using electrocardiogram waveform data that is associated with a population of individuals who are diverse in terms of age, gender, ethnicity, socioeconomic status, and the like. This approach to training allows the model to predict the presence of left and right ventricular dysfunction in a diverse population. Also introduced here is a regression framework for predicting numeric values of left ventricular ejection fraction.
    Type: Application
    Filed: April 5, 2022
    Publication date: October 5, 2023
    Inventors: Akhil VAID, Girish N. NADKARNI, Benjamin S. Glicksberg