A system for utilizing diagnostics for informed vibrant constitutional guidance includes at least a server, a diagnostic engine operating on the at least a server configured to generate a machine learning model trained by a training set, wherein the machine-learning model is configured to receive contextual information as an input and output a diagnostic output wherein the training data set includes a plurality of data entries, each data entry including at least an element of contextual information and at least a correlated diagnostic output, and at least an advisory module, operating on the at least a server configured to generate an advisory output as a function of the diagnostic output, wherein the advisory output comprises textual data identifying the diagnostic output and wherein the textual data identifying the diagnostic output is configured to be displayed on an advisor client device, and transmit the advisory output to the advisor client device.

Methods and systems are provided for a dynamically-alterable set of instructions personalized to a patient. The set of instructions may update based on patient history and/or medical professional approval. The set of instructions may keep certain portions of patient data confidential, and may dynamically trigger different workflows based on patient response.

Methods and systems are provided for a dynamically-alterable set of instructions personalized to a patient. The set of instructions may update based on patient history and/or medical professional approval. The set of instructions may keep certain portions of patient data confidential, and may dynamically trigger different workflows based on patient response.

New systems, devices, methods and other techniques for Digital Health and Digital Therapeutics are provided. In some embodiments, new techniques are provided for creating and managing personal health-related data and generating Digital Therapeutics interventions based thereon, using a new, specialized computer hardware and software control system. In some embodiments, new graphical user interfaces (“GUIs”) are provided for generating, storing and managing personal health-related data and Digital Health and Digital Therapeutics based thereon. In some embodiments, health-related data is normalized based on translation vectors. In some embodiments, standardized significance codes are defined and implemented, based on the usage of terms by user(s) of the control system. Subsequent entry of such terms during data entry by a user then causes the control system to enter data at least partially defined by such significance codes.

Mechanisms are provided for matching patients with care providers. Patient information for a current patient, from at least one patient information source, is analyzed and a medical need of the current patient is determined. Patient information for a plurality of other patients associated with a plurality of care providers is analyzed and, for each care provider in the plurality of care providers, a measure of strength for a type of medical care corresponding to the at least one medical need is determined, based on results of the analysis of patient information for the plurality of other patients associated with the care provider. At least one care provider is selected for inclusion in a care team for the current patient based on the determined strengths of each care provider in the plurality of care providers. A care team data structure comprising information about the at least one care provider is output.

Mechanisms are provided for matching patients with care providers. Patient information for a current patient, from at least one patient information source, is analyzed and a medical need of the current patient is determined. Patient information for a plurality of other patients associated with a plurality of care providers is analyzed and, for each care provider in the plurality of care providers, a measure of strength for a type of medical care corresponding to the at least one medical need is determined, based on results of the analysis of patient information for the plurality of other patients associated with the care provider. At least one care provider is selected for inclusion in a care team for the current patient based on the determined strengths of each care provider in the plurality of care providers. A care team data structure comprising information about the at least one care provider is output.

An example method for improving communication efficiency and reducing data redundancy in a computerized platform includes determining a priority value of an inquiry based on a duration of time for which the inquiry remains unanswered in the queue in comparison with other unanswered inquiries, sorting previously-obtained inquiries based on (a) a quantity of common topic labels shared between the set of topic labels associated with the inquiry and a respective set of topic labels associated with each previously-obtained inquiry in the subset and (b) a quality score associated with an answer to each previously-obtained inquiry in the subset to generate a sorted list for presentation, and routing the inquiry based on (a) user interactions, (b) the priority value of the inquiry, and (c) at least one of a user request, relation to a specialty of a healthcare professional, geographic location of the healthcare professional, or history of answers provided by the healthcare professional.

An example method for improving communication efficiency and reducing data redundancy in a computerized platform includes determining a priority value of an inquiry based on a duration of time for which the inquiry remains unanswered in the queue in comparison with other unanswered inquiries, sorting previously-obtained inquiries based on (a) a quantity of common topic labels shared between the set of topic labels associated with the inquiry and a respective set of topic labels associated with each previously-obtained inquiry in the subset and (b) a quality score associated with an answer to each previously-obtained inquiry in the subset to generate a sorted list for presentation, and routing the inquiry based on (a) user interactions, (b) the priority value of the inquiry, and (c) at least one of a user request, relation to a specialty of a healthcare professional, geographic location of the healthcare professional, or history of answers provided by the healthcare professional.

A system for geographically tracking nourishment selection including a computing device configured to receive a location from a user device associated with a user; determine a plurality of nourishment possibilities within the location; locate a performance character associated with the user, wherein the performance character contains a nourishment score; generate a user profile wherein the user profile comprises the location, the plurality of nourishment possibilities, and the performance character; generate a selector machine-learning process, wherein the selector machine-learning process utilizes the user profile as an input, and outputs a plurality of corresponding nourishment possibility indexes; and grade the plurality of nourishment possibilities using the plurality of corresponding nourishment possibility indexes.

A concept type agnostic method, system and media is provided to dynamically generate a narrative view based on the template hierarchy levels, high-level attributes of the nodes in the document template hierarchy, and end user entry is provided.