A distributed computer system comprises one or more patient system, configured to be operated by patients seeking provider services, a front-end web server to interface to the one or more patient system, a back-end server system coupled to the front-end web server to receive patient information, a healthcare provider system that provides information about a procedure needed by a patient unable to pay for the procedure, providing the information to the back-end server system, and a donor computer system, for accepting and receiving messages from the back-end server system about funding patient procedures.

A distributed computer system comprises one or more patient system, configured to be operated by patients seeking provider services, a front-end web server to interface to the one or more patient system, a back-end server system coupled to the front-end web server to receive patient information, a healthcare provider system that provides information about a procedure needed by a patient unable to pay for the procedure, providing the information to the back-end server system, and a donor computer system, for accepting and receiving messages from the back-end server system about funding patient procedures.

Disclosed herein are systems and techniques for evaluating prescribed optical devices during use. A method can include matching a user profile with a prescribed optical device, matching the prescribed optical device with a plurality of members of a distribution system of the prescribed optical device, requesting information about the prescribed optical device through a user interface, receiving information in response to requesting the information, and sending feedback based on the received information to one of the members of the distribution system. One or more network devices can generate a user interface including information associated with the prescribed optical device and the user profile. The user interface can be adapted based on a primary or secondary user of the network device. The user interface can also be adapted as the user progresses in age, treatment schedule, and/or other factors that support evaluation of the prescribed optical device.

A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.

A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.

A system for computer-aided escalation can include and/or interface with any or all of: a set of user interfaces (equivalently referred to herein as dashboards and/or hubs), a computing system, and a set of models. A method for computer-aided escalation includes any or all of: receiving a set of inputs; and processing the set of inputs to determine a set of outputs; triggering an action based on the set of outputs; and/or any other processes.

A system for computer-aided escalation can include and/or interface with any or all of: a set of user interfaces (equivalently referred to herein as dashboards and/or hubs), a computing system, and a set of models. A method for computer-aided escalation includes any or all of: receiving a set of inputs; and processing the set of inputs to determine a set of outputs; triggering an action based on the set of outputs; and/or any other processes.

Disclosed herein are methods, systems, and devices for solving the problem of caching large medical images during workflow. In one embodiment, a method is implemented on at least one computing device. The method includes receiving a source medical image file from a first remote device; caching the source medical image file in local memory; determining relevant medical image data, first non-relevant medical image data, and second non-relevant medical image data within the source medical image file; removing the second non-relevant medical image data to create a memory reduced medical image file; storing the memory reduced medical image file in the local memory; and transmitting the memory reduced medical image file to a second remote device.

A system, method and wireless earpieces for populating an electronic medical record utilizing wireless earpieces. The sensor measurements are analyzed. The sensor measurements are associated with the electronic medical record of the user. The electronic medical record of the user is populated with the sensor measurements. Communications including the electronic medical record are communicated.

A system, method and wireless earpieces for populating an electronic medical record utilizing wireless earpieces. The sensor measurements are analyzed. The sensor measurements are associated with the electronic medical record of the user. The electronic medical record of the user is populated with the sensor measurements. Communications including the electronic medical record are communicated.