IP Library Patent Application 18391616
Patent Application
App. No. 18/391,616

INTELLIGENT MEDICAL REPORT GENERATION

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Quick Facts
Patent No.
US None
App. No.
18/391,616
Abstract

Described herein are systems, methods, and programming for generating medical reports describing medical procedures. The draft medical report may include auto-generated content describing a medical procedure, where the auto-generated content may include one or more auto-generated images selected based on medical report criteria. The draft medical report may be generated and a user selection of at least one of the auto-generated images may be received. The draft medical report may be updated based on the user selection.

Claims (60)

1 . A computer-implemented method, comprising:

generating a draft medical report comprising auto-generated content describing a medical procedure, wherein the auto-generated content comprises one or more auto-generated images that have been selected based on medical report criteria;

displaying the draft medical report comprising the one or more auto-generated images;

receiving a user selection of at least one of the one or more auto-generated images; and

updating the draft medical report based on the user selection of the at least one of the one or more auto-generated images.

2 . The method of claim 1 , further comprising:

selecting a medical profile of a user associated with the medical procedure, the medical profile comprising the medical report criteria.

3 . The method of claim 1 , further comprising:

identifying one or more time windows associated with the medical procedure; and

capturing an image during at least one of the one or more time windows, wherein the one or more auto-generated images comprise the captured image.

4 . The method of claim 1 , further comprising:

obtaining a medical profile of a user associated with the medical procedure; and

identifying one or more medical report preferences of the user based on the medical profile, the one or more medical report preferences indicating time windows of the medical procedure during which the user prefers to capture images, wherein the one or more auto-generated images comprise at least some of the captured images.

5 . The method of claim 1 , further comprising:

obtaining auto-generated text describing each of the one or more auto-generated images, wherein the auto-generated content comprises the auto-generated text, and wherein the draft medical report comprises the one or more auto-generated images and the auto-generated text corresponding to each of the one or more auto-generated images.

6 . The method of claim 1 , further comprising:

displaying the updated draft medical report comprising at least some of the auto-generated content and the at least one of the one or more auto-generated images.

7 . The method of claim 1 , wherein updating the draft medical report comprises:

adding the at least one of the one or more auto-generated images to the draft medical report to obtain the updated draft medical report.

8 . The method of claim 1 , further comprising:

determining one or more medical events associated with the medical procedure based on prior performances of the medical procedure; and

generating a medical profile of a user associated with the medical procedure, the medical profile storing data indicating the one or more medical events.

9 . The method of claim 8 , further comprising:

detecting, within a video of the medical procedure, at least some of the one or more medical events; and

selecting one or more images depicting the at least some of the one or more medical events, wherein the auto-generated content comprises at least some of the one or more images.

10 . The method of claim 1 , further comprising:

training a machine learning model to identify one or more image descriptors associated with phases of the medical procedure; and

capturing, from video of the medical procedure, one or more images corresponding to the phases of the medical procedure, the auto-generated content comprising at least some of the one or more captured images.

11 . The method of claim 10 , wherein the one or more image descriptors comprise at least one of objects, environmental factors, or contextual information associated with the phases of the medical procedure.

12 . The method of claim 11 , further comprising:

generating training data comprising images that were captured during prior performances of the medical procedure for training the machine learning model; and

storing at least one of the trained machine learning model or the training data in association with a medical profile of a user that performed the medical procedure.

13 . The method of claim 11 , further comprising:

detecting, within video of the medical procedure, using the trained machine learning model, at least one of the one or more image descriptors; and

selecting one or more images from the video of the medical procedure depicting the at least one of the one or more image descriptors, the auto-generated content comprising at least some of the one or more selected images.

14 . The method of claim 1 , further comprising:

determining time windows associated with phases of the medical procedure; and

detecting an image captured at a time different than the time windows, wherein the one or more auto-generated images comprise the detected image.

15 . The method of claim 1 , further comprising:

associating audio captured during the medical procedure with an image captured during a time window associated with a phase of the medical procedure.

16 . The method of claim 1 , further comprising:

receiving user-provided text;

merging the user-provided text with auto-generated text associated with the captured image, wherein the draft medical report comprises the captured image and the merged text.

17 . The method of claim 1 , wherein generating the draft medical report comprises:

determining, based on a medical profile of a user associated with the medical procedure, one or more medical report preferences of the user; and

creating the draft medical report based on the one or more medical report preferences.

18 . The method of claim 1 , further comprising:

generating, using a machine learning model, auto-generated text for the one or more auto-generated images, wherein updating the draft medical report comprises:

adding the auto-generated text associated with at least one of the one or more auto-generated images to the updated draft medical report.

19 . A system, comprising:

one or more processors programmed to perform a method comprising:

generating a draft medical report comprising auto-generated content describing a medical procedure, wherein the auto-generated content comprises one or more auto-generated images that have been selected based on medical report criteria;

displaying the draft medical report comprising the one or more auto-generated images;

receiving a user selection of at least one of the one or more auto-generated images; and

updating the draft medical report based on the user selection of the at least one of the one or more auto-generated images.

20 . A non-transitory computer-readable medium storing computer program instructions that, when executed, effectuate a method comprising:

generating a draft medical report comprising auto-generated content describing a medical procedure, wherein the auto-generated content comprises one or more auto-generated images that have been selected based on medical report criteria;

displaying the draft medical report comprising the one or more auto-generated images;

receiving a user selection of at least one of the one or more auto-generated images; and

updating the draft medical report based on the user selection of the at least one of the one or more auto-generated images.

Assignments (1)
CHANGE OF ADDRESS Recorded Dec 18, 2024
From: STRYKER CORPORATION
To: STRYKER CORPORATION
Reel/Frame 069737/0184 →