公开(公告)号：US20220130542A1

公开(公告)日：2022-04-28

申请号：US17489441

申请日：2021-09-29

Applicant: The Regents Of The University Of Michigan

Inventor： Arvind Rao ,  Timothy Frankel

IPC: G16H50/20 ,  G06N7/00 ,  G16H20/40

Abstract: Systems and methods for using machine learning models to diagnose various diseases or conditions, as well as predict responses to various treatments. According to certain aspects, an electronic device may generate a machine learning model using training data including a set of stained cell images and/or other multi-stream data, as well as indications of any diagnosed diseases and/or whether the patients responded to specific treatments. The electronic device may access additional patient data and input the additional patient into the machine learning model. An output(s) of the machine learning model may indicate a probability(ies) of the additional patient having a disease(s) and/or a probability(ies) of the additional patient responding to a specific treatment(s).

公开(公告)号：US20250069684A1

公开(公告)日：2025-02-27

申请号：US18815472

申请日：2024-08-26

Applicant: REGENTS OF THE UNIVERSITY OF MICHIGAN

Inventor： Visweswaran Ravikumar ,  Salar Fattahi ,  Arvind Rao ,  Tong Xu

IPC: G16B5/00 ,  G16B40/30 ,  G16H20/10

Abstract: Systems for inferring spatially-varying regulatory networks, such as gene regulatory networks, are provided. Optimization processes are performed and include regularization minimization processes that rely on one or both of a smoothly-changing minimization process and a sparsely-changing minimization process, for example to learn sparsely- or smoothly-changing Gaussian Markov random fields (GMRF). The systems are further able to convert spatially-varying data, such as spatial transcriptomic data, into spatio-temporal regulatory networks.