| CPC G16H 50/30 (2018.01) [G06T 7/0012 (2013.01); G06T 2207/10081 (2013.01)] | 19 Claims |

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1. A method for evaluating health of an organ, comprising:
receiving, by one or more processors, medical image data associated with the organ, the organ comprising a thymus, the medical image data comprising a computed tomography scan;
generating a classification output, utilizing artificial intelligence, by applying a machine learning model to the received medical image data, the machine learning model trained based on a set of images associated with a plurality of thymus, at least a number of the set of images comprising labeled images, the labeled images labeled to indicate levels of fatty degeneration or non-fat attenuation in the thymus, the machine learning model generated utilizing at least supervised learning techniques;
outputting, using the one or more processors, a health score based on the classification output; and
applying a clinical solution based on the health score, the clinical solution comprising administering one or both of immunotherapy and chemotherapy.
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