Doc-Diabetes Data Analysis

Example

Analyzing weekly blood glucose readings to identify patterns and trends, such as times of day when glucose levels tend to spike or drop.

Scenario

A user uploads their SQLite database containing glucose readings. Doc processes this data to highlight times of heightened insulin sensitivity or resistance, aiding in tailoring insulin therapy.

Example

Creating graphs that plot blood glucose levels against carbohydrate intake and insulin doses, visually illustrating the effects of meals and insulin on glucose control.

Scenario

Upon receiving glucose and treatment data, Doc generates visualizations that help the user see the impact of dietary choices and insulin adjustments on their glucose levels, fostering a deeper understanding of their condition.

Example

Offering recommendations on adjusting insulin-to-carb ratios based on data analysis, aimed at optimizing blood glucose control.

Scenario

Based on analysis of past data, Doc suggests specific adjustments to a user's insulin-to-carb ratio for different meals, potentially improving glycemic outcomes.

Example

Providing explanations on how different factors affect blood glucose levels, including stress, exercise, and sleep.

Scenario

In response to observed patterns, Doc educates the user on the potential impact of lifestyle factors on blood glucose, offering guidance on how to manage these effects.