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[D] Best ML techniques over Temporal Data ?

I have a medical data set of patients ( about 50k) and each patient has around 20 – 30 records of their vitals for each hour. The Target variable is a binary variable which is 1 if the Patient contracted the Illness or 0 otherwise , so for many patients they first few row’s are 0 are and then it switches to 1 (signifying that the patient caught the illness at that point of time ).

Till now i have been treating this data as non-temporal and considering each row to be a unique record , which has been working pretty well but i would rather treat the data as temporal , any suggestions on what techniques i can use?

Also i am currently using Autoencoders to reduce the dimentionality of the data and running a CNN over the reduced data.

Thanks in advance !

submitted by /u/iholierthanthou
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.