The present invention relates to a platform for delivering an effective tapering model, comprising: a first set of instructions when executed by the processor triggers the capture and tracking of a patient's data, wherein the data includes clinical interactions at discrete points in time, compare the tracked data with the pre-determined labeled data sets of variables, wherein the data sets include pre-taper patient characteristics, identify a distinction in a time-line, construct a new taper plan by employing one or more supervised machine learning techniques, and recommend at least one potential tapering step for the patient by employing multi-label classification of neural networks.

The present invention relates to a platform for delivering an effective tapering model, comprising: a first set of instructions when executed by the processor triggers the capture and tracking of a patient's data, wherein the data includes clinical interactions at discrete points in time, compare the tracked data with the pre-determined labeled data sets of variables, wherein the data sets include pre-taper patient characteristics, identify a distinction in a time-line, construct a new taper plan by employing one or more supervised machine learning techniques, and recommend at least one potential tapering step for the patient by employing multi-label classification of neural networks.

The invention is generally related to Inflammatory Bowel Disease, Irritable Bowel Syndrome and other immune-mediated inflammatory disorders (IMIDs) such as rheumatoid arthritis, the spondyloarthritis disease spectrum, connective tissue disorders, cutaneous inflammatory conditions, asthma and autoimmune neurological diseases such as multiple sclerosis, and more particularly to compositions and methods for management and amelioration of symptoms in a subject in need thereof. One embodiment of the present invention contemplates a system and method useful for managing and ameliorating IBD symptoms resulting in the development of a personalized diet for the IBD participant which will reduce or eliminate most IBD symptoms.

The invention is generally related to Inflammatory Bowel Disease, Irritable Bowel Syndrome and other immune-mediated inflammatory disorders (IMIDs) such as rheumatoid arthritis, the spondyloarthritis disease spectrum, connective tissue disorders, cutaneous inflammatory conditions, asthma and autoimmune neurological diseases such as multiple sclerosis, and more particularly to compositions and methods for management and amelioration of symptoms in a subject in need thereof. One embodiment of the present invention contemplates a system and method useful for managing and ameliorating IBD symptoms resulting in the development of a personalized diet for the IBD participant which will reduce or eliminate most IBD symptoms.

An apparatus, including a computer including a database which stores a first electronic record and information contained in a master records file, and a distributed ledger and Blockchain technology system. The apparatus facilitates a video call between a user device and a provider device. The computer, after processing information for updating the first electronic record, processes information for identifying a plurality of second electronic records for the individual and a healthcare provider associated with each second electronic record. The computer updates each of the plurality of second electronic records, and generates a record update message. The computer transmits the record update message to each of a plurality of second provider devices associated with each second healthcare provider. Information regarding the update to the first electronic record and the update to each of the second records is stored in the distributed ledger and Blockchain technology system.

An apparatus, including a computer including a database which stores a first electronic record and information contained in a master records file, and a distributed ledger and Blockchain technology system. The apparatus facilitates a video call between a user device and a provider device. The computer, after processing information for updating the first electronic record, processes information for identifying a plurality of second electronic records for the individual and a healthcare provider associated with each second electronic record. The computer updates each of the plurality of second electronic records, and generates a record update message. The computer transmits the record update message to each of a plurality of second provider devices associated with each second healthcare provider. Information regarding the update to the first electronic record and the update to each of the second records is stored in the distributed ledger and Blockchain technology system.

The present disclosure relates to a device configuration method for configuring a diabetes management device by a diabetes management system, the diabetes management system residing on a server computer, the method comprising: receiving, by the diabetes management system, a therapy setting instruction from a computing device, validating, by the diabetes management system, the credentials of the healthcare provider by way of a validation service based on the identification information, determining, by the diabetes management system, whether the therapy setting instruction is valid based on an association between the diabetes management system, the patient, and the healthcare provider; transmitting, by the diabetes management system, one or more parameters for configuring the feature defined by the therapy setting to the subject diabetes management device; and canceling, by the diabetes management system, the therapy setting instruction in response to the therapy setting instruction being invalid. Further, a method for issuing a prescription for configuring a diabetes management device by way of a prescription system and a diabetes management system, and a diabetes management system for processing a therapy setting instruction issued by a computing device operated by a healthcare provider is provided.

The present disclosure relates to a device configuration method for configuring a diabetes management device by a diabetes management system, the diabetes management system residing on a server computer, the method comprising: receiving, by the diabetes management system, a therapy setting instruction from a computing device, validating, by the diabetes management system, the credentials of the healthcare provider by way of a validation service based on the identification information, determining, by the diabetes management system, whether the therapy setting instruction is valid based on an association between the diabetes management system, the patient, and the healthcare provider; transmitting, by the diabetes management system, one or more parameters for configuring the feature defined by the therapy setting to the subject diabetes management device; and canceling, by the diabetes management system, the therapy setting instruction in response to the therapy setting instruction being invalid. Further, a method for issuing a prescription for configuring a diabetes management device by way of a prescription system and a diabetes management system, and a diabetes management system for processing a therapy setting instruction issued by a computing device operated by a healthcare provider is provided.

Provided is a user acceptance test system and a method thereof, and the user acceptance test method includes the steps of: generating a UAT file in response to a request of a user terminal; storing the UAT file and UAT file related information; generating a UAT file list page and providing the UAT file list page to the user terminal and a manager terminal; and providing the manager terminal and/or the user terminal with the UAT file, the UAT file related information, and a communication function on a detail page linked to any one among a UAT file list on the UAT file list page.

Machine learning analysis for classifying agglutination of fluid samples. A method includes scanning a unique scannable code printed on a test card, wherein the test card comprises a negative control fluid sample, a positive control fluid sample, and a test fluid sample. The method includes capturing an image of the test card and providing the image of the test card to a machine learning algorithm configured to assess agglutination of the test fluid sample based on the image. The method includes receiving from the machine learning algorithm one or more of a qualitative analysis or a quantitative analysis of the agglutination of the test fluid sample.