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:
Aug. 04, 2026

Filed:

Mar. 28, 2023
Applicant:

Palo Alto Networks, Inc., Santa Clara, CA (US);

Inventors:

Jesse Mie Kim, Palo Alto, CA (US);

Ashwin Kumar Kannan, San Francisco, CA (US);

Anirudh Mittal, Fremont, CA (US);

William Redington Hewlett, II, Mountain View, CA (US);

Naresh Kumar Venkata Guntupalli, Fremont, CA (US);

Assignee:

Palo Alto Networks, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 10/60 (2018.01); G06F 40/279 (2020.01); G06F 40/295 (2020.01); G06N 3/045 (2023.01); G06N 3/09 (2023.01); G06N 5/01 (2023.01); G06N 20/20 (2019.01);
U.S. Cl.
CPC ...
G16H 10/60 (2018.01); G06F 40/279 (2020.01); G06N 3/045 (2023.01); G06N 3/09 (2023.01);
Abstract

A named-entity recognition (NER) model detects named entities with types that correspond to protected health information (PHI) in potentially sensitive documents. The NER model is trained to detect named entities corresponding to both personally identifiable information (PII) and medical terms. Output of the NER model is preprocessed as input to a random forest classifier that outputs a verdict that documents comprise sensitive data. The verdict is interpretable via high confidence named entities detected by the NER model that led to the verdict.


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