公开(公告)号：US20240407734A1

公开(公告)日：2024-12-12

申请号：US18737588

申请日：2024-06-07

Applicant: Dexcom, Inc.

Inventor： Jee Hye PARK ,  Spencer Troy FRANK ,  David A. PRICE ,  Charles R. STROYECK ,  Arunachalam PANCH SANTHANAM ,  Joseph J. BAKER ,  Peter C. SIMPSON ,  Kazanna C. HAMES ,  Qi AN ,  Abdulrahman JBAILY ,  Justin Yi-Kai LEE ,  Stephanie Grace MOORE

IPC: A61B5/00 ,  A61B5/145 ,  G16H50/20

Abstract: A method for predicting disease is provided. The method includes generating biased analyte data by adding analyte sensor bias to historical analyte data, associating the biased analyte data with clinical disease diagnoses associated with the historical analyte data, and extracting features from the biased analyte data. The method further includes, for each model of a number of models, generating disease predictions based on different combinations of the features extracted from the biased analyte data, and evaluating the disease predictions based on the clinical disease diagnoses associated with the biased analyte data. The method further includes selecting a model and a combination of features based on a performance metric and a robustness metric.

公开(公告)号：US20240407735A1

公开(公告)日：2024-12-12

申请号：US18737642

申请日：2024-06-07

Applicant: Dexcom, Inc.

Inventor： Spencer Troy FRANK ,  Jee Hye PARK ,  Justin Yi-Kai LEE ,  Stephanie Grace MOORE

IPC: A61B5/00 ,  A61B5/145 ,  G16H50/20

Abstract: A method for predicting gestational diabetes mellitus (GDM) is provided. The method includes, at a continuous analyte monitoring (CAM) system, measuring at least glucose concentration levels of a user, generating sensor data packages based on the measured glucose concentration levels, and transmitting the sensor data packages. The method also includes, at a computing device, receiving the sensor data packages from the CAM system, determining a glucose feature combination from the measured glucose concentration levels, and generating a GDM prediction based on the glucose feature combination. The method may also include generating a quantitative GDM risk value based on the glucose feature combination. The quantitative GDM risk value has a range from a minimum risk value to a maximum risk value.