Dynamic data-driven biological state analysis

A system comprising:

• one or more computing devices;
• and
• one or more storage devices storing instructions that are executable by the one or more computing devices and cause the one or more computing devices to perform operations comprising:
• determining a biological state for a user during a particular time period, wherein:
• the biological state is determined based on biomarker data collected for the user during the particular time period, the biomarker data comprising at least a measured glucose level and a measured ketone level, and
• the biological state is associated with a nutritional plan that the user participates in during the particular time period;
• identifying, based on the biological state, activity data representing (i) one or more terms included in messages submitted by the user on a computing device during the particular time period and (ii) one or more external actions performed by the user on the computing device during the particular time period;
• classifying, using one or more machine learning models trained to process historical account data of the user, the activity data as corresponding to a particular conversational pattern from among multiple conversational patterns associated with the biological state, wherein:
• the particular conversational pattern is classified based on the one or more external actions performed by the user on the computing device during the particular time period and a context associated with the user when performing the one or more external actions;
• determining an emotional sentiment of the user during the particular time period based on the particular conversational pattern;
• predicting a preference or an aversion to the nutritional plan by the user based on the one or more terms included in messages submitted by the user on the computing device during the particular time period;
• determining a change to a user-specific requirement associated with the nutritional plan based at least on the preference or the aversion and the emotional sentiment of the user during the particular time period;
• selecting content to provide to the user based on determining the change to the user-specific requirement associated with the nutritional plan;
• and
• providing, for output to a computing device associated with the user, a communication that includes the selected content.

At least one non-transitory computer-readable storage device storing instructions that are executable by one or more processors and cause the one or more processors to perform operations comprising:

• determining a biological state for a user during a particular time period, wherein:
• the biological state is determined based on biomarker data collected for the user during the particular time period, the biomarker data comprising at least a measured glucose level and a measured ketone level, and
• the biological state is associated with a nutritional plan that the user participates in during the particular time period;
• identifying, based on the biological state, activity data representing (i) one or more terms included in messages submitted by the user on a computing device during the particular time period and (ii) one or more external actions performed by the user on the computing device during the particular time period;
• classifying, using one or more machine learning models trained to process historical account data of the user, the activity data as corresponding to a particular conversational pattern from among multiple conversational patterns associated with the biological state, wherein:
• the particular conversational pattern is classified based on the one or more external actions performed by the user on the computing device during the particular time period and a context associated with the user when performing the one or more external actions—an emotional sentiment of the user during the particular time period based on the particular conversational;
• predicting a preference or an aversion to the nutritional plan by the user based on the one or more terms included in messages submitted by the user on the computing device during the particular time period;
• determining a change to a user-specific requirement associated with the nutritional plan based at least on the preference or the aversion and the emotional sentiment of the user during the particular time period;
• selecting content to provide to the user based on determining the change to the user-specific requirement associated with the nutritional plan;
• and
• providing, for output to a computing device associated with the user, a communication that includes the selected content.