Techniques for displaying results of computationally improved simulations

A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the process comprising:

• applying a plurality of machine learning models including a plurality of first machine learning models and a second machine learning model to features extracted from data including animal characteristics data of at least one animal, wherein the second machine learning model is a combiner model, wherein outputs of the plurality of machine learning models include a plurality of disease predictor values, wherein each disease predictor value corresponds to a respective disease type of a plurality of disease types;
• running a plurality of disease contraction simulations based on the plurality of disease predictor values;
• and
• generating at least one display element based on results of the plurality of disease contraction simulations.

A system for predictive disease identification via simulations improved using machine learning, comprising:

• a processing circuitry;
• and
• a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
• apply a plurality of machine learning models including a plurality of first machine learning models and a second machine learning model to features extracted from data including animal characteristics data of at least one animal, wherein the second machine learning model is a combiner model, wherein outputs of the plurality of machine learning models include a plurality of disease predictor values, wherein each disease predictor value corresponds to a respective disease type of a plurality of disease types;
• run a plurality of disease contraction simulations based on the plurality of disease predictor values;
• and
• generate at least one display element based on results of the plurality of disease contraction simulations.