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:
Jan. 09, 2024

Filed:

Apr. 14, 2023
Applicant:

Recovery Exploration Technologies Inc., San Francisco, CA (US);

Inventors:

Carl Bate Tulley, San Francisco, CA (US);

Wian Stipp, Somerleyton, GB;

Thomas Unger, Tiburon, CA (US);

David A. Epstein, Croton-on-Hudson, NY (US);

Matthew McSorley, Pittsburgh, PA (US);

Fady Nakhla, San Francisco, CA (US);

David Robinson, Santa Cruz, CA (US);

Jennifer May Lee, London, GB;

Arthur Böök, San Francisco, CA (US);

Assignee:

Recovery Exploration Technologies Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/40 (2020.01); G16H 70/20 (2018.01); G16H 10/60 (2018.01);
U.S. Cl.
CPC ...
G16H 70/20 (2018.01); G06F 40/40 (2020.01); G16H 10/60 (2018.01);
Abstract

A computational evidence platform extracts clinical concepts from medical evidence sources and creates a database of elemental diagnostic factors and elemental investigations links to medical conditions. Input from a person groups factors and investigations makes corrections and adds a ranking. Elemental factors and investigations do not include information specific to their associated conditions but include synonyms and a link to a medical ontology. A patient state is determined by extracting patient known diagnostic factors and investigation results from the patient chart. These known factors and results are matched to the database and a ranking of likely conditions are output. Next-best actions per condition are output by determining factors not yet known and investigations not yet performed. Next-best actions across conditions are determined by performing a recursive tree search of the database and assuming that unknown factors are now known to generate a score for each assumption.


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