A computing system for providing medication dose guidance recommendations for a query subject to treat diabetes mellitus, wherein the system comprises one or more processors and a memory, the memory comprising: - instructions that, when executed by the one or more processors, perform a method responsive to receiving a dose guidance request, the instructions comprising the steps of: a) obtaining a data structure comprising query subject parameters, b) obtaining a first data set, comprising a plurality of glucose measurements of the query subject taken over a time course and thereby establish a blood glucose history, each respective glucose measurement in the plurality of glucose measurements comprising: (i) a blood glucose level, and (ii) a corresponding blood glucose timestamp representing when in the time course the respective glucose measurement was made, c) obtaining a second data set, comprising an insulin injection history of the query subject, wherein the injection history comprises a plurality of injections during all or a portion of the time course and, for each respective injection in the plurality of injections comprising: (i) a corresponding injection amount, and (ii) an injection timestamp representing when in the time course the respective injection occurred, d) obtaining a trained model for retrospective insulin dose prediction based on blood glucose response data sets having a given retrospective horizon, e) performing data optimization for the dataset of the query subject, the data optimization including inputting query subject data to the trained model and obtaining at least one reconstructed insulin dose amount for the query subject, and f) providing a medication dose guidance recommendation, the recommendation being calculated based on data from the first data structure, the first data set, the second data set, and at least one reconstructed insulin dose amount for the query subject. - instructions that, when executed by the one or more processors, perform a method responsive to receiving a dose guidance request, the instructions comprising the steps of: a) obtaining a data structure comprising query subject parameters, b) obtaining a first data set, comprising a plurality of glucose measurements of the query subject taken over a time course and thereby establish a blood glucose history, each respective glucose measurement in the plurality of glucose measurements comprising: (i) a blood glucose level, and (ii) a corresponding blood glucose timestamp representing when in the time course the respective glucose measurement was made, c) obtaining a second data set, comprising an insulin injection history of the query subject, wherein the injection history comprises a plurality of injections during all or a portion of the time course and, for each respective injection in the plurality of injections comprising: (i) a corresponding injection amount, and (ii) an injection timestamp representing when in the time course the respective injection occurred, d) obtaining a trained model for retrospective insulin dose prediction based on blood glucose response data sets having a given retrospective horizon, e) performing data optimization for the dataset of the query subject, the data optimization including inputting query subject data to the trained model and obtaining at least one reconstructed insulin dose amount for the query subject, and f) providing a medication dose guidance recommendation, the recommendation being calculated based on data from the first data structure, the first data set, the second data set, and at least one reconstructed insulin dose amount for the query subject. a) obtaining a data structure comprising query subject parameters, b) obtaining a first data set, comprising a plurality of glucose measurements of the query subject taken over a time course and thereby establish a blood glucose history, each respective glucose measurement in the plurality of glucose measurements comprising: (i) a blood glucose level, and (ii) a corresponding blood glucose timestamp representing when in the time course the respective glucose measurement was made, (i) a blood glucose level, and (ii) a corresponding blood glucose timestamp representing when in the time course the respective glucose measurement was made, c) obtaining a second data set, comprising an insulin injection history of the query subject, wherein the injection history comprises a plurality of injections during all or a portion of the time course and, for each respective injection in the plurality of injections comprising: (i) a corresponding injection amount, and (ii) an injection timestamp representing when in the time course the respective injection occurred, (i) a corresponding injection amount, and (ii) an injection timestamp representing when in the time course the respective injection occurred, d) obtaining a trained model for retrospective insulin dose prediction based on blood glucose response data sets having a given retrospective horizon, e) performing data optimization for the dataset of the query subject, the data optimization including inputting query subject data to the trained model and obtaining at least one reconstructed insulin dose amount for the query subject, and f) providing a medication dose guidance recommendation, the recommendation being calculated based on data from the first data structure, the first data set, the second data set, and at least one reconstructed insulin dose amount for the query subject.