The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 08, 2024

Filed:

Dec. 19, 2023
Applicant:

Blaize, Inc., El Dorado Hills, CA (US);

Inventors:

Deepak Chandra Bijalwan, Hyderabad, IN;

Dinakar C. Munagala, El Dorado Hills, CA (US);

Assignee:

Blaize, Inc., El Dorado Hills, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06T 5/70 (2024.01); G06T 7/00 (2017.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06F 18/214 (2023.01); G06F 18/2163 (2023.01); G06F 18/217 (2023.01); G06N 3/08 (2013.01); G06T 5/70 (2024.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.


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