I've been logging my daily activity for some time now. I have a huge dataset, including:
- Very detailed log of food intake (including timestamps and milligram-precise nutritional information).
- Activity (calories spend, coming from an "life-hack" app that tracks my location using GPS).
- Location x Time (same app).
- Sleep/Wakeup time, including waking up mid night (I log it using another app).
- From those I can also infer time working, watching TV, etc.
- Water intake (just weight/day, from measuring a bottle once per day).
- Body weight (measured daily).
- Migraine episodes (start time, duration).
- Blood pressure, blood sugar and body temperature, measured 4 times a day.
- Mood, also 4 times a day.
- Bathroom usage.
- Additional activities such as sex, sports, gaming are logged too.
For anyone wondering, I'm doing this mostly for practicing programming and learning. It's being a cool project, but I wonder if I can somehow find correlations between that data. For example, I'd love to know if an specific food is somehow linked to the migraine episodes. I'd also love to know random trivia such as "if you eat at morning you are much more likely to have good mood at afternoon", or "eating X grams of sugar at once always makes you want to nap".
Is there any way artificial intelligence can help me on that?
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