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[Discussion] Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction

I’ve been reading through Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction (Author’s GitHub repo) and I found it quite interesting. My field is more general event stream processing rather than medical but I am thinking this approach is worth exploring.

I’ve not seen this paper discussed before so I thought I’d raise it here and ask what peoples thoughts are.

Unfortunately for me, I can’t access the source data to reproduce their results (since you need to be in the medical field to access Physionet data) and Chinese is totally foreign to me so I’ve had to use the help of Google Translate with the couple of PDF files I found in the GH repo that explain the data format).

I’ve gone through and annotated the file format to help me at least understand it better – may be useful for others trying to explore this: Annotated data format

submitted by /u/jarym
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.