Abstract: A system is provided for maintaining sterile fields in a monitored enclosure. Multi-modal sensor data associated with a subject performing a plurality of actions within a monitored enclosure is correlated. The multi-modal sensor data is received at defined time intervals from a plurality of sensing devices located within the monitored enclosure. The subject is authorized to selectively perform a set of designated tasks based on contextual analysis of the correlated multi-modal sensor data, the set of parameters retrieved from a data store, and/or a set of activities performed by the subject. A notification is generated, via a portable device associated with an unauthorized subject, based on detection of an event associated with an unauthorized action performed by the unauthorized subject.

Abstract: Computer-implemented tools, techniques, and algorithms are provided for meeting financial targets in connection with medical procedures (e.g., surgical operations) performed by a healthcare entity. A method for restructuring classification of multiple medical procedures for a healthcare entity may be provided in which medical procedure data including charge related data are collected in association with multiple patient encounters for a medical procedure. A data model is created from the collected data and a predetermined number of procedure charge levels are generated each in association with an acuity resource value range. Each medical procedure is then reclassified into one of the procedure charge levels in accordance with at least one level assignment rule. This reclassification can then be processed to determine whether it results in a predetermined desired data distribution and/or meets financial targets for the medical procedure charge data.

Abstract: 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.

Abstract: A method and a system include at least one processor of a plurality of computing devices that execute a plurality of heart disease triage (HDT) microservices operating on a scalable data container orchestration platform. The platform is configured to continuously receive a plurality of patient-specific data files that include medical data and provider visit data for each patient. Patient-specific diagnostic text of the medical history, the provider visit, and echocardiogram data in the patient-specific data files of patients identified as having echocardiogram data are tokenized using a feature-space transformation to generate a patient-specific tokenized diagnostic feature set. The patient-specific tokenized diagnostic feature set for each identified patient is inputted to an HD severity determination machine learning model to generate a heart disease (HD) severity score.