US 11,748,884 B2
Method for hospital visit guidance for medical treatment for active thyroid eye disease, and system for performing same
Kyubo Shin, Ulsan (KR); Jaemin Park, Busan (KR); and Jongchan Kim, Ulsan (KR)
Assigned to THYROSCOPE INC., Ulsan (KR)
Filed by THYROSCOPE INC., Ulsan (KR)
Filed on Jan. 6, 2023, as Appl. No. 18/94,064.
Application 18/094,064 is a continuation of application No. 17/939,040, filed on Sep. 7, 2022, granted, now 11,663,719.
Application 17/939,040 is a continuation of application No. PCT/KR2022/009356, filed on Jun. 29, 2022.
Claims priority of application No. 10-2021-0085542 (KR), filed on Jun. 30, 2021; and application No. 10-2022-0079770 (KR), filed on Jun. 29, 2022.
Prior Publication US 2023/0153999 A1, May 18, 2023
Int. Cl. G06T 7/00 (2017.01); G06T 7/70 (2017.01); G06T 7/12 (2017.01); A61B 5/00 (2006.01); A61B 3/14 (2006.01); G16H 50/20 (2018.01)
CPC G06T 7/0012 (2013.01) [A61B 3/14 (2013.01); A61B 5/4227 (2013.01); A61B 5/445 (2013.01); A61B 5/4824 (2013.01); A61B 5/4878 (2013.01); G06T 7/12 (2017.01); G06T 7/70 (2017.01); G16H 50/20 (2018.01); G06T 2207/20021 (2013.01); G06T 2207/20132 (2013.01); G06T 2207/30041 (2013.01); G06T 2207/30201 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method of managing a thyroid eye disease, comprising:
outputting a first screen for receiving an evaluation of a user's subjective pain through a user terminal;
based on a prestored score determination algorithm and a first user input, calculating a score of a spontaneous retrobulbar pain and a score of a pain on attempted upward or downward gaze, wherein the first user input comprises an input obtained as a response to the first screen;
outputting a second screen for receiving a facial image, wherein, at the second screen, a photograph guide appears on the user terminal such that at least one eye of the user appears on the facial image;
based on one or more sign prediction models and the facial image, obtaining a score of a conjunctival hyperemia, a score of a conjunctival edema, a score of a lacrimal edema, a score of an eyelid redness and a score of an eyelid edema, wherein the one or more sign prediction models is pretrained with a training data set that comprises clinical images captured on a hospital and a doctor's judgments on the clinical images;
calculating a final score by adding the scores of the spontaneous retrobulbar pain, the pain on attempted upward or downward gaze, the conjunctival hyperemia, the conjunctival edema, the lacrimal edema, the eyelid redness, and the eyelid edema with a same weight; and
determining whether the user is recommended to visit a hospital by comparing the final score and final criteria.