公开(公告)号：US20220240864A1

公开(公告)日：2022-08-04

申请号：US17619449

申请日：2020-06-16

Applicant: The Trustees of Princeton University

Inventor： Hongxu Yin ,  Bilal Mukadam ,  Xiaoliang Dai ,  Niraj K. Jha

IPC: A61B5/00 ,  G06N3/04 ,  A61B5/0205 ,  G06N3/08

Abstract: According to various embodiments, a machine-learning based system for diabetes analysis is disclosed. The system includes one or more processors configured to interact with a plurality of wearable medical sensors (WMSs). The processors are configured to receive physiological data from the WMSs and demographic data from a user interface. The processors are further configured to train at least one neural network based on a grow-and-prune paradigm to generate at least one diabetes inference model. The neural network grows at least one of connections and neurons based on gradient information and prunes away at least one of connections and neurons based on magnitude information. The processors are also configured to output a diabetes-based decision by inputting the received physiological data and demographic data into the generated diabetes inference model.

公开(公告)号：US11521068B2

公开(公告)日：2022-12-06

申请号：US16760209

申请日：2018-10-25

Applicant: The Trustees of Princeton University

Inventor： Xiaoliang Dai ,  Hongxu Yin ,  Niraj K. Jha

IPC: G06N3/08 ,  G06N3/04

Abstract: According to various embodiments, a method for generating one or more optimal neural network architectures is disclosed. The method includes providing an initial seed neural network architecture and utilizing sequential phases to synthesize the neural network until a desired neural network architecture is reached. The phases include a gradient-based growth phase and a magnitude-based pruning phase.

公开(公告)号：US10798238B2

公开(公告)日：2020-10-06

申请号：US16340930

申请日：2017-10-13

Applicant: The Trustees of Princeton University

Inventor： Arsalan Mosenia ,  Xiaoliang Dai ,  Prateek Mittal ,  Niraj K. Jha

IPC: H04W24/00 ,  H04M1/725 ,  H04W4/029 ,  G01C21/20 ,  G01C21/30 ,  H04W64/00 ,  H04M15/00 ,  H04W4/30 ,  H04W4/02

Abstract: According to various embodiments, a method for locating the user of a mobile device without accessing global position system (GPS) data is disclosed. The method includes determining the last location that the user was connected to a wireless network. The method further includes compiling publicly-available auxiliary information related to the last location. The method additionally includes classifying an activity of the user to driving, traveling on a plane, traveling on a train, or walking. The method also includes estimating the location of the user based on sensory and non-sensory data of the mobile device particular to the activity classification of the user.

公开(公告)号：US20190289125A1

公开(公告)日：2019-09-19

申请号：US16340930

申请日：2017-10-13

Applicant: The Trustees of Princeton University

Inventor： Arsalan Mosenia ,  Xiaoliang Dai ,  Prateek Mittal ,  Niraj K. Jha

IPC: H04M1/725 ,  G01C21/20 ,  G01C21/30 ,  H04W4/029 ,  H04W64/00

Abstract: According to various embodiments, a method for locating the user of a mobile device without accessing global position system (GPS) data is disclosed. The method includes determining the last location that the user was connected to a wireless network. The method further includes compiling publicly-available auxiliary information related to the last location. The method additionally includes classifying an activity of the user to driving, traveling on a plane, traveling on a train, or walking. The method also includes estimating the location of the user based on sensory and non-sensory data of the mobile device particular to the activity classification of the user.