US 12,293,832 B2
System and method for predicting the risk of future lung cancer
George R. Washko, Jr., West Roxbury, MA (US); Christopher Scott Stevenson, West Sussex (GB); Samuel Yoffe Ash, Newton, MA (US); Raul San Jose Estepar, Wellesley, MA (US); and Matthew David Mailman, New Hope, PA (US)
Assigned to Johnson & Johnson Enterprise Innovation Inc., New Brunswick, NJ (US)
Filed by Johnson & Johnson Enterprise Innovation Inc., New Brunswick, NJ (US)
Filed on Jul. 13, 2022, as Appl. No. 17/863,978.
Claims priority of provisional application 63/328,590, filed on Apr. 7, 2022.
Claims priority of provisional application 63/222,712, filed on Jul. 16, 2021.
Prior Publication US 2023/0027734 A1, Jan. 26, 2023
Int. Cl. G16H 50/30 (2018.01); G06T 7/00 (2017.01); G06V 10/44 (2022.01); G06V 10/50 (2022.01); G06V 10/774 (2022.01); G16H 50/20 (2018.01)
CPC G16H 50/20 (2018.01) [G06T 7/0016 (2013.01); G06V 10/44 (2022.01); G06V 10/50 (2022.01); G06V 10/774 (2022.01); G16H 50/30 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30064 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/03 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method for predicting one or more risks of lung cancer for a subject, the method comprising:
obtaining one or more images captured from the subject;
extracting features from the one or more obtained images, the extracted features including at least one of a longitudinal lung parenchyma feature associated with an absence of nodules or a longitudinal body composition feature associated with an absence of nodules; and
predicting one or more risks of lung cancer for the subject based on a risk prediction model trained to analyze the extracted features from the one or more obtained images and generate a predicted score indicating a likelihood of the subject developing lung cancer.