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. 12, 2021

Filed:

Oct. 03, 2017
Applicant:

Hvh Precision Analytics Llc, King of Prussia, PA (US);

Inventors:

Oodaye Shukla, Chesterbrook, PA (US);

Amy Finkbiner, King of Prussia, PA (US);

Robert Lauer, Phoenixville, PA (US);

Cody Garges, Chalfont, PA (US);

Rauf Izmailov, King of Prussia, PA (US);

Ritu Chadha, King of Prussia, PA (US);

Cho-Yu Jason Chiang, King of Prussia, PA (US);

Assignee:

HVH PRECISION ANALYTICS LLC, King of Prussia, PA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06K 9/62 (2006.01); G06N 7/00 (2006.01); G16H 10/60 (2018.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G16H 50/70 (2018.01); G06K 9/6256 (2013.01); G06K 9/6269 (2013.01); G06N 7/005 (2013.01); G06N 20/00 (2019.01); G16H 10/60 (2018.01);
Abstract

A method, computer program product, and system identifying a probability of a medical condition in a patient. The method includes a processor obtaining data set(s) related to a patient population diagnosed with a medical condition and based on a frequency of features in the data set(s), identifying common features. The processor generates pattern(s) including a portion of the common features to generate a machine learning algorithm(s). The processor compiles a training set of data to use to tune the machine learning algorithm(s). The processor dynamically adjusts common features in the pattern(s) such that the machine learning algorithm(s) can distinguish patient data indicating the medical condition from patient data not indicating the medical condition. The processor applies the machine learning algorithm(s) to data related to the undiagnosed patient, to determine the probability.


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