Inspiration

Attempted to use techniques that are on the DL side, more than traditional ML techniques

What it does

Created clusters based on unstructured text with medical references

How we built it

Used LSTM and tSNE, then LDA to obtain most important terms

Challenges we ran into

Building a working LSTM network, treating the original text, choosing number of words to consider, difficulty to clearly understand the cases

Accomplishments that we're proud of

Clusters were created based on data without labels

What we learned

Combining DL with tSNE and LDA later

What's next for La FrancoArgentina - Similar Patients

https://github.com/dtorresdho/bitsxlaMarato

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