A method for supporting hospital visits on a social network platform includes: detecting a user input for registering a visit at a hospital using a social network client application of the social network platform; in response to detecting the user input: obtaining a registration number for the visit, wherein the registration number indicates an ordinal position of the user in a hospital queue of multiple visitors to the hospital; and displaying a group chat interface for a group conversation including a social network identity of the user and a public social network identity of the hospital; and displaying a payment request for the visit in the group chat interface.

An anonymization processing device that anonymizes input data and outputs anonymized output data, includes an input unit configured to receive the input data; a processing unit configured to anonymize the input data, to generate anonymized data corresponding to the input data that has been anonymized; a first storage unit configured to store the anonymized data; and an output unit configured, in a case where a plurality of anonymized data items stored in the first storage unit satisfy an anonymity index, to generate and output a plurality of output data items corresponding to the anonymized data items, respectively, and to delete the anonymized data items from the first storage unit.

A method to securely transfer data to aid in a medical procedure or to a data management system to be accessed in a medical care facility is provided that includes a set of data from a data storage system being downloaded via a network to a visible light communication (VLC) enabled device. The set of data from the VLC enabled device is then transferred to a VLC enabled device located in an operating room (OR) via point to point VLC or uploaded to a data management system. The transferred set of data is then used to aid in a medical procedure or be accessed by a medical care facility. Software executables are similarly transferred and run in an OR context.

A data analysis system according to the present invention includes: a training data acquisition unit that acquires a combination of training data including information about a medicinal drug and a plurality of pieces of classification information for classifying the training data on the basis of a plurality of classification standards; a learning unit that learns a pattern of the information about the medicinal drug from distribution of data elements which constitute at least part of the training data and appear according to the classification information; an unknown data acquisition unit that acquires unknown data from a specified information source; a data evaluation unit that evaluates the acquired unknown data on the basis of the learned pattern with respect to each of the plurality of classification standards; and a presentation unit that presents the information about the medicinal drug included in the unknown data to a user according to evaluation by the data evaluation unit.

A data analysis system according to the present invention includes: a training data acquisition unit that acquires a combination of training data including information about a medicinal drug and a plurality of pieces of classification information for classifying the training data on the basis of a plurality of classification standards; a learning unit that learns a pattern of the information about the medicinal drug from distribution of data elements which constitute at least part of the training data and appear according to the classification information; an unknown data acquisition unit that acquires unknown data from a specified information source; a data evaluation unit that evaluates the acquired unknown data on the basis of the learned pattern with respect to each of the plurality of classification standards; and a presentation unit that presents the information about the medicinal drug included in the unknown data to a user according to evaluation by the data evaluation unit.

A virtual object display system includes a plurality of head-mounted displays 1 each having a virtual object acquisition unit 22 that acquires a virtual object, a display information acquisition unit 23 that acquires display information used to display the virtual object, and a display control unit 24 that causes a display unit to display the virtual object on the basis of the display information, and enables switching between of first display control for causing the virtual object to be displayed on the basis of display information acquired by each of the plurality of head-mounted displays 1 and second display control for causing the virtual object having an identical orientation to an orientation of the virtual object displayed on the basis of display information acquired by another head-mounted display 1 to be displayed.

A computer-implemented method comprising: outputting questions to a user via one or more user devices, and receiving back responses to some of the questions from the user via one or more user devices; over time, controlling the outputting of the questions so as to output the questions under circumstances of different values for each of one or more items of metadata, wherein the one or more items of metadata comprise at least a time and/or a location at which a question was output to the user via the one or more user devices; monitoring whether or not the user responds when the question is output with the different metadata values; training the machine learning algorithm to learn a value of each of the items of metadata which optimizes a reward function, and based thereon selecting a time and/or location at which to output subsequent questions.

Disclosed herein are a health device, a gateway device, and a method for securing a protocol using the health device and the gateway device. The method includes performing, by the health device and the gateway device, authentication and key exchange based on security session information; sending, by any one of the health device and the gateway device, an application message protected based on the security session information; and receiving, by a remaining one of the health device and the gateway device, the protected application message.

Systems and methods to improve the optical character recognition of records, and in particular health records, are provided. An image of a medical record is received, and an initial optical image recognition (OCR) on the image is performed to identify text information. The OCR signal quality may be measured, and areas of insufficient OCR signal quality may be isolated. The signal quality is determined by a weighted average of semantic analysis of the resulting text, and/or OCR accuracy measures. The OCR process may be repeated on the isolated regions of lower signal quality, each time using a different OCR transform, until all regions are completed with a desired degree of signal quality (accuracy). All the regions of the document may then be recompiled into a single document for outputting.

Systems and methods to automatically generate classifiers are provided. A labeled dataset is initially received. The dataset may be for a positive class, or may be a negative for a class, or a false positive class. N features that are predictive for the class (or false positive or the negative class) are identified. These features are combined within a classifier dictionary. Medical records received may be processed in order to be machine readable. Features within the medical records are identified and are compared against the dictionary of classifiers. Matches indicate classes within the medical record. The classifier dictionary may be periodically updated in response to insufficient classification accuracy, or when new data becomes available.