Systems for determining similarity of sequences of glucose values

1 . A method implemented by a computing device, the method comprising:

receiving input data describing a sequence of user glucose values measured by a continuous glucose monitoring (CGM) system, the sequence of user glucose values including subsequences of user glucose values;

accessing sequence data describing a plurality of sequences of glucose values, each sequence of the plurality of sequences including subsequences of glucose values;

identifying a particular sequence of the plurality of sequences of glucose values that is similar to the sequence of user glucose values based on a comparison between each of the subsequences of user glucose values and every subsequence of glucose values included in the particular sequence, wherein the comparison includes determining a difference between a probability of observing a first glucose value included in a subsequence of user glucose values based on context data and a probability of observing a second glucose value included in a subsequence of glucose values included in the particular sequence based on the context data;

determining an externality associated with the particular sequence; and

generating an indication of the externality for display in a user interface.

2 . The method as described in claim 1 , wherein the externality is described by metadata associated with the particular sequence.

3 . The method as described in claim 1 , wherein the externality is an adverse event that is likely to occur if an intervention is not conducted and wherein the indication of the externality includes an indication of the intervention.

4 . The method as described in claim 1 , wherein the externality is an adverse event that was likely to occur if the sequence of user glucose values is not similar to the particular sequence.

5 . The method as described in claim 4 , wherein the indication of the externality includes a counterfactual indication.

6 . The method as described in claim 1 , wherein the sequence of user glucose values is associated with a particular user and the plurality of sequences of glucose values are associated with the particular user.

7 . The method as described in claim 1 , wherein the sequence of user glucose values is associated with a particular user and the plurality of sequences of glucose values are associated with a different user.

8 . The method as described in claim 7 , wherein the plurality of sequences of glucose values are associated with multiple different users.

9 . The method as described in claim 1 , wherein the context data describes a glucose value before or after the first glucose value in the one subsequence of user glucose values.

10 . The method as described in claim 1 , wherein the context data describes a glucose value before or after the second glucose value in the one subsequence of glucose values.

11 . A method implemented by a computing device, the method comprising:

receiving input data describing a sequence of user glucose values measured by a continuous glucose monitoring (CGM) system;

computing similarity scores for a plurality of sequences of glucose values by comparing each glucose value included in the sequence of user glucose values with every glucose value included in each sequence of the plurality of sequences, wherein the comparing includes determining a difference between a probability of observing a first glucose value included in the sequence of user glucose values based on context data and a probability of observing a second glucose value included in the particular sequence based on the context data;

identifying a particular sequence of glucose values of the plurality of sequences that is associated with a highest similarity score of the similarity scores;

determining an externality associated with the particular sequence; and

generating an indication of the externality for display in a user interface.

12 . The method as described in claim 11 , wherein the sequence of user glucose values is associated with a particular user and the plurality of sequences of glucose values are associated with the particular user.

13 . The method as described in claim 11 , wherein the sequence of user glucose values is associated with a particular user and the plurality of sequences of glucose values are associated with multiple different users.

14 . The method as described in claim 11 , wherein the context data describes a glucose value before or after the first glucose value in the sequence of user glucose values.

15 . The method as described in claim 11 , wherein the context data describes a glucose value before or after the second glucose value in the particular sequence.

16 . A method implemented by a computing device, the method comprising:

receiving input data describing a sequence of user glucose values measured by a continuous glucose monitoring (CGM) system;

determining a difference between a probability of observing each glucose value included in the sequence of user glucose values based on context data and a probability of observing each glucose value included in a candidate sequence of glucose values based on the context data;

computing a similarity score for the candidate sequence by summing the determined differences;

comparing the similarity score to a similarity threshold score; and

generating, in response to the similarity score being greater than the similarity threshold score, an indication of the candidate sequence for display in a user interface.

17 . The method as described in claim 16 , further comprising:

determining an externality associated with the candidate sequence; and

generating an indication of the externality for display in the user interface.

18 . The method as described in claim 17 , wherein the indication of the externality includes a counterfactual indication.