Let's say I have a medical dataset/EHR dataset that is retrospective and longitudinal in nature. Meaning one person has multiple measurements across multiple time points (in the past).
This dataset contains information about patients' diagnosis, labs, admissions, and drugs consumed, etc.
Now, if I would like to find out predictors that can influence mortality, I can use logistic regression (whether the patient will die or not).
But my objective is to find out what are the predictors that can help me predict whether a person will die in the next 30 days or the next 240 days, how can I do this using ML/Data Analysis techniques?
In addition, I would also like to compute a score that can indicate the likelihood that this person will die in the next 30 days? How can I compute the scores? Any tutorial, please?
Can you help with this please?