US 12,354,749 B2
Machine learning models for automated diagnosis of disease database entities
Joshua Reicher, Albany, CA (US); and Michael Muelly, Sunnyvale, CA (US)
Assigned to Imvaria Inc., Berkeley, CA (US)
Filed by Imvaria Inc., Berkeley, CA (US)
Filed on Jul. 12, 2022, as Appl. No. 17/862,553.
Prior Publication US 2024/0020825 A1, Jan. 18, 2024
Int. Cl. G16H 50/20 (2018.01); G06T 7/00 (2017.01); G06T 11/00 (2006.01); G16H 30/40 (2018.01)
CPC G16H 50/20 (2018.01) [G06T 7/0012 (2013.01); G06T 11/008 (2013.01); G16H 30/40 (2018.01); G06T 2207/10081 (2013.01); G06V 2201/03 (2022.01)] 10 Claims
OG exemplary drawing
 
1. A method of automated diagnosis of disease database entities, the method comprising:
receiving a case processing request from at least one of a medical data storage system and an electronic case submission interface via an input application programming interface (API), wherein the case processing request includes at least one medical scan image and at least one medical data entry associated with a patient;
extracting image data from the case processing request, the image data including at least one medical scan image of the patient;
extracting at least one of text data and lab data from the case processing request, the at least one of text data and lab data associated with a medical condition of the patient;
selecting at least a portion of the medical scan image(s) according to specified selection criteria;
normalizing the selected at least a portion of the medical scan image(s);
converting the selected at least a portion of the medical scan image(s) to at least one mathematical representation for processing by a machine learning model implementation;
supplying the at least one mathematical representation to a machine learning model to generate a target medical condition prediction output, wherein the target medical condition prediction output is indicative of a likelihood that a patient will experience a future disease diagnosis event corresponding to the target medical condition; and
automatically transmitting the target medical condition prediction output as an electronic transmission via an output API to a provider system associated with the patient.
 
2. The method of claim 1, wherein the at least one medical scan image includes a computed tomography (CT) scan, and the target medical condition includes interstitial lung disease (ILD).