Conformal prediction techniques to classify histopathology images based on possible diagnostic entities, with calibrated confidence levels

A system for processing of a histopathology image, the system comprising:

• at least one computer hardware processor;
• and
• at least one non-transitory computer readable storage medium, storing processor executable instructions, that when executed by the at least one computer hardware processor cause the processor to perform a method comprising:
• obtaining the histopathology image, the image containing histopathology data of one or more tissue samples;
• processing the histopathology image data using at least one trained machine learning (ML) model to determine a likelihood of one or more diagnostic entities being present in the one or more tissue samples;
• determining a calibrated probability for each of the determined likelihoods of diagnostic entities being present;
• generating an output set of one or more diagnostic entities, wherein a size of the output set and the diagnostic entities within the output set are determined based on the calibrated probabilities associated with each diagnostic entity;
• and
• causing a user interface to display the output set and indications of the one or more diagnostic entities of the output set.

At least one non-transitory computer readable storage medium, storing processor executable instructions, that when executed by at least one computer hardware processor cause the processor to perform a method comprising:

• obtaining a histopathology image, the image containing histopathology data of one or more tissue samples;
• processing the histopathology image data using at least one trained machine learning (ML) model to determine a likelihood of one or more diagnostic entities being present in the one or more tissue samples;
• determining a calibrated probability for each of the determined likelihoods of diagnostic entities being present;
• generating an output set of one or more diagnostic entities, wherein a size of the output set and the diagnostic entities within the output set are determined based on the calibrated probabilities associated with each diagnostic entity;
• and
• causing a user interface to display the output set and indications of the one or more diagnostic entities of the output set.