Systems and methods for generating pet likelihood scores for diseases, clinical conditions and traits

A computer system for identifying a likelihood of a pet developing at least one of a disease, a clinical condition or other trait, the computer system comprising:

• at least one processor;
• and
• at least one memory storing instructions that are executable by the at least one processor, cause the at least one processor to:
• receive pet data associated with the pet, wherein the pet data includes genetic data and breed data;
• generate, by applying the pet data to a trained machine learning model, a likelihood score for the pet associated with the clinical condition, wherein the trained machine learning model is trained to predict likelihood scores for the at least one of the disease, the clinical condition or other trait;
• and
• cause a visual representation of the likelihood score to be displayed on a user device, wherein the visual representation includes an indication of the likelihood of the pet developing the at least one of the disease, the clinical condition or other trait.

A non-transitory computer-readable medium storing computer-executable instructions which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• receiving pet data associated with the pet, wherein the pet data includes genetic data and breed data;
• generating a likelihood score for the pet associated with at least one of a disease, a clinical condition or other trait by applying the pet data to a trained machine learning model, wherein the trained machine learning model is trained to predict likelihood scores for the at least one of the disease, the clinical condition or other trait;
• and
• causing a visual representation of the likelihood score to be displayed on a user device, wherein the visual representation includes an indication of a likelihood of the pet developing the at least one of the disease, the clinical condition or other trait.