A portable data processing device for forming a wireless network includes a chamber configured within a housing; a microprocessor; a power supply; a sensor communicatively coupled to the microprocessor; and data storage media; and a wireless communication module. The microprocessor is configured to broadcast, by the wireless communication module, a device identification signal; listen for an external device identification signal; transmit device capability data; receive external device capability data. The microprocessor is further configured to receive an internal measurement from the sensor; transmit the internal measurement; receive an external measurement from the external device; analyze the internal measurement and the external measurement to determine an analysis result; and transmit the analysis result.

A system and method for manufacturing custom fit artificial nails includes a 3D surface scanning module and a 3D printing module and use thereof. A central processing module is connected to the 3D surface scanning module and the 3D printing module and performs: operating the 3D surface scanning module to obtain an image of a user's hands/feet; processing the image to create an input 3D model of nails of the user; generating an output 3D model corresponding to artificial nails matching dimensions of the user's nails according to the 3D input model; operating the 3D printing module to manufacture artificial nails according to the output 3D model; and generating medical data by correlating the identified features of the user's nails with known medical conditions, in order to diagnose a medical condition of the user which is known to exhibit the identified features as a symptom. Alternatively, or additionally, medicinal ingredient may be included in the artificial nail to treat the medical condition of the user. Embedded devices, sensors or an RFID chip may be integrated into the artificial nail.

The disclosure provides a system that may receive an identification of a first patient; may receive a first template that includes first multiple locations associated with a face of the first patient and associated with the identification of the first patient; may determine second multiple locations associated with a face of a current patient; may determine a second template of the face of the current patient based at least on the second multiple locations associated with the face of the current patient; may determine if the first template matches the second template; if the first template matches the second template, may provide an indication that the current patient has been correctly identified as the first patient; and if the first template does not match the second template, may provide an indication that the current patient has not been identified.

The disclosure provides a system that may receive an identification of a first patient; may receive a first template that includes first multiple locations associated with a face of the first patient and associated with the identification of the first patient; may determine second multiple locations associated with a face of a current patient; may determine a second template of the face of the current patient based at least on the second multiple locations associated with the face of the current patient; may determine if the first template matches the second template; if the first template matches the second template, may provide an indication that the current patient has been correctly identified as the first patient; and if the first template does not match the second template, may provide an indication that the current patient has not been identified.

A system and method for automatic capturing of physician and patient interaction time and location information during provision of medical services by a physician during an appointment with a patient in hospitals, offices or clinics. Capturing total interaction time facilitates verifiable physician reimbursement by third-party payers. RF beacon technology based on the Bluetooth Low Energy devices and communications protocol may be utilized for personnel and location identification. The use of store-and-forward communications enable both reliable interaction-tracking packet data communications to an external host IT system in online offices, and alternatively the queuing of all data for transmission to an off-line host computer.

Aspects of the subject disclosure may include, for example, a method that includes receiving, by a processing system including a processor coupled to a communication network, data regarding participation by a network subscriber in a public health program. The data includes a real-time report of an event relating to the subscriber participation, and is sent from subscriber equipment to a base station of the communication network via a dedicated information element. The method also includes determining a rate of participation in the program by a population of a community in a coverage area of the base station. The method further includes training a model for participation in the program by members of the community; the training comprises applying machine learning to the model. The method also includes adjusting the model in accordance with the data; administration of the program is modified in accordance with the model. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, a method that includes receiving, by a processing system including a processor coupled to a communication network, data regarding participation by a network subscriber in a public health program. The data includes a real-time report of an event relating to the subscriber participation, and is sent from subscriber equipment to a base station of the communication network via a dedicated information element. The method also includes determining a rate of participation in the program by a population of a community in a coverage area of the base station. The method further includes training a model for participation in the program by members of the community; the training comprises applying machine learning to the model. The method also includes adjusting the model in accordance with the data; administration of the program is modified in accordance with the model. Other embodiments are disclosed.

Techniques for addressing various technical problems associated with managing medical data are described herein. One or more medical data tracking applications can execute on an electronic medical data tracking system. Such a computer system can include one more computing devices, such as for example a mobile computing device and a central computing system, that can optionally communicate with each other to send and receive information associated with a patient. The mobile computing device can be configured as an employee identification card, and can be configured to detect and identify patients, gestures, medical devices, and medicine associated with medical procedures.

Techniques for addressing various technical problems associated with managing medical data are described herein. One or more medical data tracking applications can execute on an electronic medical data tracking system. Such a computer system can include one more computing devices, such as for example a mobile computing device and a central computing system, that can optionally communicate with each other to send and receive information associated with a patient. The mobile computing device can be configured as an employee identification card, and can be configured to detect and identify patients, gestures, medical devices, and medicine associated with medical procedures.

The present invention relates to an electrocardiogram analysis matching support service system that supports timely and real-time analysis of an individual's electrocardiogram, and it is characterized in that it includes: a patient service app module that is installed and executed in a patient's mobile communication terminal, transmits an electrocardiogram measurement data received from a wearable electrocardiogram measurement device, requests for reading, and receives and displays the result of the reading; and a patient and medical staff matching server that reads the electrocardiogram measurement data transmitted from the patient service app module using a deep learning trained artificial intelligence network model, selects pre-registered medical staff according to the result of the reading, and supports reading the electrocardiogram measurement data.