US 12,444,510 B2
Medical assessment based on voice
Jangwon Kim, Los Angeles, CA (US); Namhee Kwon, Manhattan Beach, CA (US); Henry O'Connell, Spanish Fork, UT (US); Phillip Walstad, Provo, UT (US); and Kevin Shengbin Yang, Boston, MA (US)
Assigned to Canary Speech, Inc., Provo, UT (US)
Filed by Canary Speech, Inc., Provo, UT (US)
Filed on Jun. 13, 2024, as Appl. No. 18/742,032.
Application 18/742,032 is a continuation of application No. 18/347,382, filed on Jul. 5, 2023, granted, now 12,051,513.
Application 18/347,382 is a continuation of application No. 17/827,970, filed on May 30, 2022, granted, now 11,756,693, issued on Sep. 12, 2023.
Application 17/827,970 is a continuation of application No. 16/422,718, filed on May 24, 2019, granted, now 11,348,694, issued on May 31, 2022.
Application 16/422,718 is a continuation of application No. 15/973,504, filed on May 7, 2018, granted, now 10,311,980, issued on Jun. 4, 2019.
Claims priority of provisional application 62/502,584, filed on May 5, 2017.
Claims priority of provisional application 62/614,192, filed on Jan. 5, 2018.
Prior Publication US 2024/0331882 A1, Oct. 3, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 80/00 (2018.01); A61B 5/00 (2006.01); A61B 5/11 (2006.01); G06N 3/08 (2023.01); G06N 7/01 (2023.01); G06N 20/10 (2019.01); G10L 25/66 (2013.01); G16H 10/20 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06F 111/10 (2020.01); G10L 15/02 (2006.01); G10L 15/06 (2013.01); G10L 15/22 (2006.01)
CPC G16H 80/00 (2018.01) [A61B 5/1123 (2013.01); A61B 5/4088 (2013.01); A61B 5/4803 (2013.01); A61B 5/7267 (2013.01); G06N 3/08 (2013.01); G06N 7/01 (2023.01); G06N 20/10 (2019.01); G10L 25/66 (2013.01); G16H 10/20 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06F 2111/10 (2020.01); G10L 15/02 (2013.01); G10L 15/063 (2013.01); G10L 15/22 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for training a mathematical model for detecting a medical condition, the system comprising at least one computer configured to:
obtain a training corpus comprising data items, wherein each data item is labelled with a diagnosis value and wherein the training corpus comprises speech data items and non-speech data items, the non-speech data items comprising demographic information, medical history information, or a combination thereof;
compute a plurality of features for each data item in the training corpus;
compute a feature selection score for each feature of the plurality of features, wherein:
the feature selection score for a feature indicates a usefulness of the feature for detecting the medical condition, and
the feature selection score is computed using, for each data item, a value of the feature and the diagnosis value corresponding to the data item;
select a subset of the plurality of features using the feature selection scores;
train the mathematical model for detecting the medical condition using the subset of the plurality of features for each data item of the training corpus;
deploy a computer program product or computer service for detecting the medical condition using the mathematical model;
present, by the computer program product or computer service, a prompt to a person;
receive, by the computer program product or computer service, a prompted data item corresponding to the person in response to the prompt;
compute a medical diagnosis score by processing the prompted data item using the mathematical model; and
display, by the computer program product or computer service, one or more of the medical diagnosis score or a medical diagnosis based on the medical diagnosis score.