Provided is a medical image processing apparatus including: an image acquisition unit that obtains a medical image of a subject; and an image processing unit that generates a second medical image by applying predetermined image processing on the medical image. The image processing unit includes: a surface area extraction unit that extracts a surface area including information that can lead to individuality determination or identification of the subject, from the medical image; a body orientation determination unit that determines body orientation on the basis of the surface area; a surface area deformation unit that deforms the surface area of the medical image; and an object assignment unit that assigns an object indicating the body orientation to the medical image in which the surface area has been deformed and that generates the second medical image.

A method includes receiving a scheduling request that identifies a medical consumable, accessing first document types that indicate how often medical consumables are to be ingested, identifying a frequency at which the first designated medical consumable is to be consumed based on the first document types, accessing second document types that indicate a pattern of personal activity behavior, identifying one or more temporal opportunity windows based on the second document types, determining one or more matches between the frequency at which the first designated medical consumable is to be consumed and the one or more temporal opportunity windows, creating an adherence schedule based on the one or more matches that indicates when reminders to ingest the first designated medical consumable are to be generated, and generating one or more of the reminders to ingest the first designated medical consumable on a mobile electronic device according to the adherence schedule.

A method includes receiving a scheduling request that identifies a medical consumable, accessing first document types that indicate how often medical consumables are to be ingested, identifying a frequency at which the first designated medical consumable is to be consumed based on the first document types, accessing second document types that indicate a pattern of personal activity behavior, identifying one or more temporal opportunity windows based on the second document types, determining one or more matches between the frequency at which the first designated medical consumable is to be consumed and the one or more temporal opportunity windows, creating an adherence schedule based on the one or more matches that indicates when reminders to ingest the first designated medical consumable are to be generated, and generating one or more of the reminders to ingest the first designated medical consumable on a mobile electronic device according to the adherence schedule.

Embodiments of the disclosure provide a method for aggregating and providing health data records to an electronic device. The method is performed by a server that includes a processor and a non-transitory computer readable medium with processor-executable instructions stored thereon. When the instructions are executed by the processor, the server performs the method including: (a) receiving collected data from one or more client devices, the collected data comprising health related data including at least one of step count data, heart rate data, sleep sensor data; (b) extracting metadata from the collected data; (c) pseudonymizing the collected data; (d) categorizing the collected data using the extracted metadata and enterprise ontology of the server; and (e) storing the collected data.

A server computing device generates a virtual patient object (VPO) from a patient health record. The server computing device generates documents based upon the VPO. The server computing device causes a term-document index to be generated based upon the documents, the term-document index mapping terms in text of the documents to identifiers for the documents in which the terms are found. Subsequently, responsive to receiving a textual query from a client computing device, the server computing device executes a textual search over the term-document index based upon the textual query. The textual search produces search results that comprise an identifier for a document in the documents that includes a term specified in the textual query. The server computing device identifies a portion of the VPO based upon the search results and transmits the portion of the VPO to the client computing device for display.

A diagnostic imaging support system includes: an image input unit that receives an input of an image; a first processing unit that detects a region of interest including a subject of interest from the image, classifies the detected region of interest, and outputs a first classification result; and a second processing unit that subjects the region of interest to semantic segmentation, classifies the region of interest based on a result of the semantic segmentation, and outputs a second classification result. When a predetermined condition related to the region of interest is met, the first classification result is employed as indicating a class of the region of interest, and, when the condition is not met, the second classification result is employed as indicating the class of the region of interest.

A method of managing insulin includes receiving blood glucose measurements on a computing device from a glucometer. The blood glucose measurements are separated by a time interval. The method includes determining, by the computing device, an insulin dose rate based on the blood glucose measurements and determining a blood glucose drop rate based on the blood glucose measurements and the time interval. The method also includes determining a blood glucose percentage drop based on the blood glucose measurements. The method includes decreasing the time interval between blood glucose measurements by the glucometer when the blood glucose drop rate is greater than a threshold drop rate, and decreasing the time interval between blood glucose measurements by the glucometer when the blood glucose percentage drop is greater than a threshold percentage drop.

A method of managing insulin includes receiving blood glucose measurements on a computing device from a glucometer. The blood glucose measurements are separated by a time interval. The method includes determining, by the computing device, an insulin dose rate based on the blood glucose measurements and determining a blood glucose drop rate based on the blood glucose measurements and the time interval. The method also includes determining a blood glucose percentage drop based on the blood glucose measurements. The method includes decreasing the time interval between blood glucose measurements by the glucometer when the blood glucose drop rate is greater than a threshold drop rate, and decreasing the time interval between blood glucose measurements by the glucometer when the blood glucose percentage drop is greater than a threshold percentage drop.

A medical data authentication system, a medical data authentication method, and a computer program product thereof are disclosed, The medical data authentication system includes a data establishment module, a signature module, a blockchain establishment module, and an authorization code generation module. The data establishment module is used for establishing a medical data. The signature module is used for receiving the medical data to obtain a medical digital signature. The blockchain establishment module is used for uploading the medical digital signature to a medical blockchain. The authorization code generation module is used for obtaining the medical digital signature from the medical blockchain to generate a corresponding authentication authorization code.

A medical data authentication system, a medical data authentication method, and a computer program product thereof are disclosed, The medical data authentication system includes a data establishment module, a signature module, a blockchain establishment module, and an authorization code generation module. The data establishment module is used for establishing a medical data. The signature module is used for receiving the medical data to obtain a medical digital signature. The blockchain establishment module is used for uploading the medical digital signature to a medical blockchain. The authorization code generation module is used for obtaining the medical digital signature from the medical blockchain to generate a corresponding authentication authorization code.