Abstract: Described herein is a graphical intervention test development system. The graphical intervention test development system provides a graphical intervention test development environment that facilitates computer-based design of an intervention test. The graphical intervention test development environment provides a graphical user interface (GUI) and visualizations of various aspects of an intervention test therein. The graphical intervention test development environment further provides a control interface through which a user can manipulate control parameters that affect outcomes of the intervention test.

Abstract: A model-assisted system for determining a patient event date may include a processor. The processor may be programmed to access a database storing a medical record associated with a patient, the medical record comprising unstructured data; analyze the unstructured data to identify a plurality of snippets of information in the medical record associated with a patient event; determine a date associated with each of the plurality of snippets, identify a plurality of query periods associated with the patient event; and generate, for each of the query periods, a probability of whether the patient event occurred during the query period based on the plurality of snippets and the associated dates.

Abstract: A model-assisted system for determining a patient event date may include a processor. The processor may be programmed to access a database storing a medical record associated with a patient, the medical record comprising unstructured data; analyze the unstructured data to identify a plurality of snippets of information in the medical record associated with a patient event; determine a date associated with each of the plurality of snippets, identify a plurality of query periods associated with the patient event; and generate, for each of the query periods, a probability of whether the patient event occurred during the query period based on the plurality of snippets and the associated dates.

Abstract: A model-assisted system for identifying a group of patients for a cohort using a generalized biomarker model may include a processor programmed to provide, to a generalized biomarker model, a first biomarker associated with a cohort, the generalized biomarker model being trained based on one or more second biomarkers; receive, from the generalized biomarker model, an output indicating a plurality of individuals with associated likelihoods of at least one of: having an attribute associated with the third biomarker or having been tested for the attribute associated with the first biomarker; determine a likelihood threshold based on a predetermined cohort size associated with the first biomarker and identify, based on the output, a group of the plurality of individuals for inclusion in a cohort, each individual in the group of the plurality of individuals being associated with a likelihood received from the generalized biomarker model that satisfies the likelihood threshold.