Patents by Inventor Smadar SHILO

Smadar SHILO 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).

  • METHOD AND SYSTEM FOR PREDICTING ANALYTE LEVELS
    Publication number: 20230076246
    Abstract: A method of predicting an analyte level comprises receiving a time-ordered series of levels of the analyte, monitored over a time-period; feeding a trained neural network procedure with the monitored levels; and displaying, based on an output received from the procedure, a predicted level of the analyte in a future time. The procedure can comprise a plurality of layers, wherein for at least one pair of layers, a number of inter-layer connections within the pair is higher for later monitored levels than for earlier monitored levels.
    Type: Application
    Filed: February 17, 2020
    Publication date: March 9, 2023
    Applicants: Yeda Research and Development Co. Ltd., Mor Research Applications Ltd.
    Inventors: Eran SEGAL, Smadar SHILO, Yotam AMAR
  • METHOD AND SYSTEM FOR PREDICTING GESTATIONAL DIABETES
    Publication number: 20220328185
    Abstract: A method of predicting likelihood for gestational diabetes, comprises: obtaining a plurality of parameters characterizing a female subject, accessing a computer readable medium storing a machine learning procedure trained for predicting likelihoods for gestational diabetes, feeding the procedure with the plurality of parameters, and receiving from the procedure an output indicative of a likelihood that the subject has, or expected to develop, gestational diabetes, wherein the output indicative is related non-linearly to the parameters.
    Type: Application
    Filed: May 24, 2020
    Publication date: October 13, 2022
    Applicant: Yeda Research and Development Co. Ltd.
    Inventors: Eran SEGAL, Smadar SHILO, Nitzan ARTZI
  • METHOD AND SYSTEM FOR PREDICTING CHILDHOOD OBESITY
    Publication number: 20210038166
    Abstract: A method of predicting likelihood for childhood obesity, comprises: obtaining a plurality of parameters, wherein at least a few of the parameters characterize an infant or toddler subject. A machine learning procedure trained for predicting likelihoods for childhood obesity is feed with the plurality of parameters. An output indicative of a likelihood that the infant or toddler subject is expected to develop childhood obesity is received from the procedure. The output is related non-linearly to the parameters.
    Type: Application
    Filed: August 5, 2020
    Publication date: February 11, 2021
    Applicant: Yeda Research and Development Co. Ltd.
    Inventors: Eran SEGAL, Smadar SHILO, Hagai ROSSMAN