Systems and methods for processing electronic medical images to optimize a review order of pathology cases

A system for processing electronic medical images, the system comprising:

• at least one memory storing instructions;
• and
• at least one processor configured to execute the instructions to perform operations comprising:
• receiving a plurality of variables and one or more constraints, wherein the plurality of variables are bounded by the one or more constraints;
• receiving a plurality of pathology cases, each case of the plurality of pathology cases including one or more medical images of at least one pathology specimen associated with a patient;
• providing the one or more medical images from each case, the plurality of variables, and the one or more constraints as input to a trained machine learning system, the trained machine learning system having been trained to predict a sequential order for user review of the plurality of pathology cases based on a plurality of medical images, a plurality of training variables, and a plurality of training constraints;
• receiving, as an output of the trained machine learning system, the sequential order for user review of the plurality of pathology cases;
• and
• automatically providing each case of the plurality of pathology cases to a user for review according to the sequential order.

A non-transitory computer-readable medium storing instructions that, when executed by a processor, perform operations processing electronic medical images, the operations comprising:

• receiving a plurality of variables and one or more constraints, wherein:
• the plurality of variables including at least one of a pathologist preference, a number of cases to be reviewed per day, pathologist expertise, a diagnosis quality, a time of day, a day of week, pathologist behavior, a client expectation, and a laboratory consideration, and
• the one or more constraints including at least one of pathologist availability, pathologist qualifications, a case deadline, a time available, and a department goal;
• receiving a plurality of pathology cases, each case of the plurality of pathology cases including one or more medical images of at least one pathology specimen associated with a patient;
• providing the one or more medical images from each case, the plurality of variables, and the one or more constraints as inputs to a trained machine learning system, wherein:
• the plurality of variables are bounded by the one or more constraints, and
• the trained machine learning system having been trained to predict a sequential order for user review of the plurality of pathology cases based on a plurality of medical images, a plurality of training variables, and a plurality of training constraints;
• receiving, as an output of the trained machine learning system, the sequential order for user review of the plurality of pathology cases to optimize one or more of the plurality of variables based on the one or more constraints;
• and
• automatically providing each case of the plurality of pathology cases to a user for review according to the sequential order.