US 11,894,143 B2
System and methods for integrating animal health records
Debra Leon, Long Grove, IL (US); Trevor Page, Chicago, IL (US); and Gunnison Carbone, Orlando, FL (US)
Assigned to Whiskers Worldwide, LLC, Skokie, IL (US)
Filed by Whiskers Worldwide, LLC, Skokie, IL (US)
Filed on Mar. 6, 2020, as Appl. No. 16/811,606.
Application 16/811,606 is a continuation in part of application No. 15/359,033, filed on Nov. 22, 2016, granted, now 10,629,304.
Application 15/359,033 is a continuation in part of application No. 14/011,538, filed on Aug. 27, 2013, abandoned.
Prior Publication US 2020/0203019 A1, Jun. 25, 2020
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 50/30 (2018.01); G16H 10/60 (2018.01); G06N 20/10 (2019.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06N 3/08 (2023.01)
CPC G16H 50/30 (2018.01) [G06N 20/10 (2019.01); G16H 10/60 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for outputting a condition of an animal comprising:
maintaining, at a server, a health record for the animal, said health record linked to a global record set in a database, said global record set including data corresponding to a global animal population;
capturing unstructured information including pet data and human owner data from one or more remote client devices through self-service functions and from one or more healthcare providers associated with the animal;
updating the health record with the pet data and the human owner data, said human owner data including diabetic information corresponding to a human owner of the animal;
generating one or more condition records corresponding to said updated health record, each condition record associated with a symptom of the animal;
analyzing each condition record to assess the condition of the animal, wherein each condition record is analyzed on an individual basis and in regard to the global population to make a dimensional projection based on the pet data and the human owner data;
predicting a medical condition of the animal based on the pet data and the human owner data, wherein the predicting comprises training a machine learning model based on the analyzing of each condition record, wherein said predicting further includes comparing a weight of said animal to the model for a probabilistic determination of initial onset of diabetes; and
transmitting an output related to the condition of the animal to the one or more client devices, wherein the output includes at least one of a cause, a treatment, and an outcome.