A method includes: receiving, by a computer device, an association of a prescribed treatment to a user; receiving, by the computer device, an image of the user; receiving, by the computer device, an image of treatment adherence by the user; determining, by the computer device, adherence to the prescribed treatment by analyzing the image of treatment adherence; and generating, by the computer device, a personalized visualization illustrating the determined adherence to the prescribed treatment by modifying the image of the user.

A method includes: receiving, by a computer device, an association of a prescribed treatment to a user; receiving, by the computer device, an image of the user; receiving, by the computer device, an image of treatment adherence by the user; determining, by the computer device, adherence to the prescribed treatment by analyzing the image of treatment adherence; and generating, by the computer device, a personalized visualization illustrating the determined adherence to the prescribed treatment by modifying the image of the user.

A method to perform automatic corneal topography or tomography difference mapping includes receiving one or more corneal topography or tomography data files and/or a corneal image for an examined patient from a corneal topography or tomography system; receiving personal identification parameters from captured user personal data communicated from the corneal topography or tomography system; and comparing received patient identification parameters to existing patient identification parameters in a database to identify if there are existing topography or tomography data files for a same patient in the database. The method may further include retrieving a prior topography or tomography data file for the patient from the database; and performing difference mapping by comparing the received topography or tomography data files to the prior topography or tomography data file retrieved from the database to generate a topography or tomography difference map.

A method to perform automatic corneal topography or tomography difference mapping includes receiving one or more corneal topography or tomography data files and/or a corneal image for an examined patient from a corneal topography or tomography system; receiving personal identification parameters from captured user personal data communicated from the corneal topography or tomography system; and comparing received patient identification parameters to existing patient identification parameters in a database to identify if there are existing topography or tomography data files for a same patient in the database. The method may further include retrieving a prior topography or tomography data file for the patient from the database; and performing difference mapping by comparing the received topography or tomography data files to the prior topography or tomography data file retrieved from the database to generate a topography or tomography difference map.

Diagnosis is inferred by using at least one of a plurality of inferencers configured to infer diagnosis from a medical image and by using a medical image as an input into the at least one of the plurality of inferencers, and the inferred diagnosis is represented.

A computer-implemented method for providing a radiological opinion includes the steps of: (a) receiving an order for a radiological opinion by means of a web-based application accessible to a user; (b) launching an upload/scan application accessible to the user; (c) scanning a user-selected folder or drive for DICOM images; (d) parsing the DICOM images found in step (c); (e) uploading the DICOM images parsed in step (d); (f) routing the uploaded DICOM images to a picture archiving communication system; (g) generating a radiology order; (h) routing the radiology order to a radiology information system; (i) receiving a radiological opinion; (j) routing the radiological opinion to the user and (k) receiving electronic payment from the user following a successful upload of the radiological opinion, the electronic payment being governed by blockchain technology.

A method, computer program product, and computing system for tracking encounter participants is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information obtained via one or more machine vision systems. The machine vision encounter information is processed to identify one or more humanoid shapes.

A method, computer program product, and computing system for tracking encounter participants is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information obtained via one or more machine vision systems. The machine vision encounter information is processed to identify one or more humanoid shapes.

Systems and methods are disclosed for providing automated routing of medical data, comprising determining at least one rule corresponding to at least one condition and at least one receiver, receiving medical data and associated medical metadata, determining whether the medical data, the associated medical metadata, and/or associated artificial intelligence processing satisfies the at least one condition of the at least one rule, and upon determining that the at least one condition of the at least one rule is satisfied, providing, from an originating institution, the medical data to the at least one receiver.

A system and method for analyzing a data store of de-identified patient data to generate one or more dynamic user interfaces usable to predict an expected response of a particular patient population or cohort when provided with a certain treatment. The automated analysis of patterns occurring in patient clinical, molecular, phenotypic, and response data, as facilitated by the various user interfaces, provides an efficient, intuitive way for clinicians to evaluate large data sets to aid in the potential discovery of insights of therapeutic significance.