I am doctor using dataiku to analyse my patients database.
I have one column containing the diagnosis date. And another column containing the date of death, if this column is empty, it means that at the current time , the patient is still alive.
I am looking for a way to generate the survival curve
For exemple with a Kaplan Meier estimator
But without leaving DSS
I scrolled across the discussions but no did not find anything so far.
I have no Python programming skill
Thank you for your help.
I do not know of a built-in way to do Survival Analysis.
If I were doing this I'd likely create an R notebook and use a R libraries that dose Survival Analysis.
There are a bunch of internet posts on doing survival analysis with R
Someone in the dataiku community called @aabraham proposed to pluginify this function.
We are currently defining the needs.
As soon as the solution will be available I will post it here and close this topic as resolved .
Tom, I sent you a private message regarding this plugin ;).
I had some custom recipes to fit a Kaplan-Meier model in DSS and I turned it into a plugin adapted to the usage of David. It relies on the python lifelines plugin and does only KM but it could use any default method provided in lifelines. This plugin is very rough, it does not handle errors and it is not supported by dataiku in any way. If you are interested, let me know and I can send it to you.
I have joined the plugin I have created which is a very basic plugin allowing to run Kaplan Meier estimator on data. It is from my own initiative, on my free time, so it is in no way related to or supported by Dataiku. There is no documentation because the usage is very straightforward: You must give an integer duration (duration of observation) and a boolean column to indicate if the event (usually death) happend or not. A condition column also allow to run the estimator on several conditions in a single dataset.
Let me know if you use it so that I can warn you when the official survival analysis plugin is out!