[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 !