Intact Medical Notes NLP Project

Inspiration

The inspiration was from how hospitals/insurance companies could quickly determine patient needs.

What it does

The project is able to preprocess the medical transcriptions to make it more usable for machine learning. This involes using tokenizing, stemming, stop words and lemmatizing the raw data.

How we built it

We learned how to use python, spacy, NLTK and pandas.

Challenges we ran into

We ran into time constraint problems while learning on the fly.

Accomplishments that we're proud of

We learned about the NLP pipeline and the basics of machine learning. We learned how to use python, spacy, NLTK and pandas.

What we learned

We learned about the NLP pipeline and the basics of machine learning.

What's next for Intact Medical Notes NLP Project

Next would be to determine what machine learning model to use as well as implement it. Next time we could try using tf-idf, word2vec etc.

Built With

• nltk
• pandas
• python
• spacy