You can find medcat here.

Of course, please go ahead.

I can send the paper if needed. Regarding the timeline view - you are exactly right, and yes this is just a quick demo, new features will be coming out in the following months (this is a research tool, nothing commercial).

We take all free text from a hospital EHR (done using CogStack a data harmonization platform for hospitals) and extract disorders, symptoms, medications and all relevant biomedical concepts using MedCAT. Then create the timelines, enrich them with any structured data we might have access to and train the models.

Thank you for the feedback.

We did not explore intrinsic biases in the data, like doctors prescribing a certain medication or giving a certain diagnosis because of someone's social status, or because something is more common or anything else. This for sure happens, there are many papers talking about these problems in healthcare, and we in fact think that the model (foresight) can be used to explore biases in the data. In the future, we hope to resolve this by training the models also on medical guidelines and biomedical literature - so not just hospital text.

We did analyse the predictions for problems like the model always predicting the most common concepts or the simplest concepts. I will add a histogram of the F1 scores over different concepts to the paper, but it does show that the model predicts a very wide range of different concepts accurately. We've also done a manual analysis, where 5 clinicians checked the model predictions - and in fact, the model is better at predicting complex and strange cases. But, this is expected because forecasting someone's future and saying they will have the flu in 3 months is nearly impossible.

Hi, we did not do that but will mark it down for the next iteration. During the manual tests, we did not see any obvious biases or problems given ethnicity/sex but probably good to make a quantitative analysis.