Question: Risk score stratification with k-means
gravatar for julia.gilhodes
5 weeks ago by
julia.gilhodes0 wrote:

Dear all,

I have created a risk score (point-based risk score) to predict time to brain metastases from covariates selected with a backward approach. My risk score ranges from 0 to 45. I need to classify my patients into 4 risk groups:low/intermediate low/ intermediate high/high. My question is: can I use a clustering approach like k-means, by including my clinical characteristics and my risk score, to obtain clusters with similar risk scores and clinical characteristics?

Thank you in advance for your help.

risk score cut-off cluster • 98 views
ADD COMMENTlink modified 4 weeks ago by Kevin Blighe61k • written 5 weeks ago by julia.gilhodes0
gravatar for Mensur Dlakic
5 weeks ago by
Mensur Dlakic5.8k
Mensur Dlakic5.8k wrote:

A general answer to your question is yes. In practice, it depends on how many features (clinical characteristics) and data points (patients) you have. It also matters what you plan to do with these clusters: are they just for internal bookkeeping or for future diagnostics? If you are planning to classify/diagnose new patients, I think it may be better to do a formal machine learning approach with (cross)validation, and test it on unseen data. That will also depend on the number of data points and informative features.

There is a great risk of overfitting if you simply cluster based on presently available data, especially if the dataset size is small.

ADD COMMENTlink written 5 weeks ago by Mensur Dlakic5.8k
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