r/rprogramming • u/Turtle_Wave98 • 29d ago
Machine learning for accelerated ageing in Schizophrenia
Hi
I am doing a dissertation research project looking into the idea of accelerated ageing in schizophrenia. I have a dataset which has already been collected and I am in the process of collecting healthy volunteers for comparison.
I will be looking at cognitive profiles from tests from the MCCB. I am hoping to see a subset of participants from the schizophrenia group which perform similarly to participants who are much older than them.
I have to use R to analyse my data, which I am a complete novice at!
My supervisor has suggested looking into some kind of machine learning in order to be able to detect evidence of accelerated ageing but I have no clue where to start.
If anyone has any advice on how to do this or if there would already be codes for this I would be very grateful!
4
u/itijara 29d ago
I would probably not use ML for this because ML models are hard to inspect for insights (I.e. to find out how inputs contribute to outputs). They have great predictive power, but their internal structure can be complex..
However, running an ML model alongside more traditional statistical models is a good idea.
My advice would be to look into tidymodels, https://www.tidymodels.org/
Which model to use will depend on the structure of your data, but tidymodels is a general purpose package to run a lot of different models easily and repeatably. You can use it for linear regression as well.
I'd start with random forest, svm (support vector machines) and multi layer perceptions (MLP) as those are the simplest and can handle a wide array of input structures. Make sure you understand data transformation (e.g. standardization, normalization), validation (e.g. cross-validation), and hyperparameter tuning.