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:
Jul. 14, 2026

Filed:

Feb. 23, 2023
Applicant:

Ainnocence Technologies Llc, Miami, FL (US);

Inventors:

Yutong Jin, Zhengzhou City, CN;

Lurong Pan, Vestavia Hill, AL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16B 15/30 (2019.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G16C 20/50 (2019.01); G16C 20/70 (2019.01); G16C 20/80 (2019.01); G16C 10/00 (2019.01); G16C 20/30 (2019.01);
U.S. Cl.
CPC ...
G16B 15/30 (2019.02); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G16C 20/50 (2019.02); G16C 20/70 (2019.02); G16C 20/80 (2019.02); G16C 10/00 (2019.02); G16C 20/30 (2019.02);
Abstract

A drug screening model construction method and device, a screening method, apparatus and a medium, in the field of drug screening that includes obtaining a drug training set, where the set comprises a chemical formula of a drug protein, a chemical formula of a small molecule and a classification label; drawing an initial graph network of drug protein and small molecule, in which atoms are nodes and chemical bonds are edges connecting nodes; using a random initialization vector to identify the weight vector of each node; reconstructing each node of the initial graph network according to the connection relationship of the initial graph network to obtain a reconstruction network, and repeating the reconstruction steps to obtain at least two layers of reconstruction networks; performing deep learning on the initial graph network and the reconstruction graph network according to the classification labels, and constructing a drug screening model.


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