A non-transitory computer-readable medium, containing instructions for causing a computing environment to perform a method of operating and tuning or adapting a decision-support application that forms a part of a continuous glucose monitoring, CGM, application running on a smart device, the tuning or adapting performed in a way to support user-desired functionality to maintain the user's blood glucose level within a target range, the method comprising steps of: receiving an indication of user-desired functionality to maintain the user's blood glucose level within the target range; receiving insulin delivery data and an insulin sensitivity for the user; tuning or adapting the decision-support application to support the user-desired functionality, such that the tuning or adapting results in an insulin dose recommendation to maintain the user's blood glucose level within the target range on a user interface at least partially supported by the decision-support application to be based on the user-desired functionality and on input real-time data; wherein the real-time data comprises continuous glucose monitor, CGM, data from a sensor forming part of a continuous glucose monitor, and further comprises fuzzy input meal data entered by the user, the fuzzy input meal data being a user categorization of a content of a meal; and wherein the tuning or adapting comprises determining based on the fuzzy input meal data, a corresponding quantitative carbohydrate value, wherein the correspondence between the fuzzy input meal data and the corresponding carbohydrate value is learned using machine-learning from the user's glucose response for previous fuzzy input meal data, and wherein the insulin dose recommendation to maintain the user's blood glucose level within the target range is further based on the CGM data, the insulin delivery data, the insulin sensitivity and the carbohydrate value. receiving an indication of user-desired functionality to maintain the user's blood glucose level within the target range; receiving insulin delivery data and an insulin sensitivity for the user; tuning or adapting the decision-support application to support the user-desired functionality, such that the tuning or adapting results in an insulin dose recommendation to maintain the user's blood glucose level within the target range on a user interface at least partially supported by the decision-support application to be based on the user-desired functionality and on input real-time data; wherein the real-time data comprises continuous glucose monitor, CGM, data from a sensor forming part of a continuous glucose monitor, and further comprises fuzzy input meal data entered by the user, the fuzzy input meal data being a user categorization of a content of a meal; and wherein the tuning or adapting comprises determining based on the fuzzy input meal data, a corresponding quantitative carbohydrate value, wherein the correspondence between the fuzzy input meal data and the corresponding carbohydrate value is learned using machine-learning from the user's glucose response for previous fuzzy input meal data, and wherein the insulin dose recommendation to maintain the user's blood glucose level within the target range is further based on the CGM data, the insulin delivery data, the insulin sensitivity and the carbohydrate value.