Systems and methods for disease control and management

A computer-implemented method for creating and updating one or more models for providing personalized notifications for health conditions, the method comprising:

• receiving, using a receiver of a disease management server, weight measurements from a weight measuring device wirelessly connected to the disease management server, and user data of the user, from a user device;
• executing, using one or more processors of the disease management server, a basic model of a physiological system generic to any user to generate a modified model specific to a physiological system of the user, wherein generating the modified model comprises updating the basic model based on information specific to the user;
• performing, using the one or more processors, a statistical analysis to detect a data excursion in the received weight measurements, wherein a data excursion is detected when a weight measurement, of the received weight measurements, collected at a particular time, is outside of a predetermined range;
• executing, using the one or more processors, the modified model to generate personalized notifications, based on the modified model, wherein executing the modified model comprises determining one or more factors causing a detected data excursion, and developing the personalized notifications based on the determined one or more factors that caused a detected data excursion, the personalized notifications including adjusting a timing of obtaining weight measurements;
• generating, using the one or more processors, an updated modified model, at least once, based on the modified model, wherein generating the updated modified model comprises training the modified model with the determined one or more factors learned from the received weight measurements to update an ability of the modified model, in the updated modified model, to estimate an impact of changes in the one or more factors on the physiological system of the user;
• performing, using the one or more processors, the statistical analysis to detect a data excursion in received additional weight measurements, wherein a data excursion in the received additional weight measurements is detected when a weight measurement, of the received additional weight measurements, collected at a particular time, is outside of the predetermined range;
• executing the updated modified model to generate updated personalized notifications, wherein executing the updated modified model comprises determining one or more factors causing a detected data excursion in the received additional weight measurements, and developing the updated personalized notifications based on the determined one or more factors that caused a detected data excursion in the received additional weight measurements, the updated personalized notifications including adjusting a timing of obtaining weight measurements;
• and
• outputting the personalized notifications and the updated personalized notifications to at least one of the weight measuring device and the user device;
• and
• outputting, using the weight measuring device or the user device, the personalized notifications and the updated personalized notifications to the user.

A system for creating and updating one or more modified models for providing personalized notifications for health conditions, comprising:

• a glucose measuring device configured to obtain glucose measurements from a user, and to wirelessly transmit the obtained glucose measurements;
• a weight measuring device configured to obtain weight measurements from the user, and to wirelessly transmit the obtained weight measurements;
• and
• a disease management server in wireless communication with the glucose measuring device and the weight measuring device, the disease management server comprising:
• a receiver for receiving the glucose measurements, the weight measurements, and user data, from a user device;
• and
• one or more processors configured to:
• execute a basic model of a physiological system generic to any user to generate one or more modified models specific to a physiological system of the user, wherein generating the one or more modified models comprises updating the basic model based on information specific to the user;
• perform a statistical analysis to detect a data excursion in at least one of the received glucose measurements and the received weight measurements, wherein a data excursion is detected when a glucose measurement, of the received glucose measurements, collected at a particular time, is outside of a predetermined range of glucose measurements, or a weight measurement, of the received weight measurements, is outside of a predetermined range of weight measurements;
• execute the one or more modified models to generate personalized notifications, based on the one or more modified models, wherein executing the one or more modified models comprises determining one or more factors causing a detected data excursion, and developing the personalized notifications based on the determined one or more factors that caused a detected data excursion, the personalized treatment recommendations including one or more of adjusting a timing of obtaining the glucose measurements and adjusting a timing of obtaining the weight measurements;
• generate one or more updated modified models, based on the one or more modified models, wherein generating the one or more updated modified models comprises training the one or more modified models with the determined one or more factors learned from the received glucose measurements and the received weight measurements, to update an ability of the one or more modified models, in the corresponding one or more updated modified models, to estimate an impact of changes in the one or more factors on the physiological system of the user;
• perform the statistical analysis to detect a data excursion in at least one of received additional glucose measurements and additional weight measurements, wherein a data excursion is detected when a glucose measurement, of the received additional glucose measurements, collected at a particular time, is outside of the predetermined range of glucose measurements, or a weight measurement, of the received additional weight measurements, is outside of the predetermined range of weight measurements;
• execute the one or more updated modified models, to generate updated personalized notifications, wherein executing the one or more updated modified models comprises determining one or more factors causing a detected data excursion in the at least one of the received additional glucose measurements and the additional weight measurements, and developing the updated personalized notifications based on the determined one or more factors that caused a detected data excursion in the received additional glucose measurements or the additional weight measurements, the updated personalized notifications including at least one of adjusting a timing of obtaining the glucose measurements and adjusting a timing of obtaining the weight measurements;
• and
• output the personalized notifications and the updated personalized notifications to at least one of the glucose measuring device, the weight measuring device, and the user device,
• wherein each of the glucose measuring device, the weight measuring device, and the user device is further configured to receive and to output the personalized notifications and the updated personalized notifications to the user.