AI in Health group project in collaboration with Dr. Yifan Peng from Cornell Medicine.
The research project focuses on exploring different possibilities to build a successful model that can classify the type of relation type available in a sentence of medical text. In our research, we utilized a variety of feature extraction methods such as TF-IDF, Bag-of-Words, Word2Vec, Spacy, BERT, and Sentence-BERT. For the classification task, we implemented models such as Decision Tree, Random Forest, Long Short Term Memory model et cetera. We found that in our smaller datasets, simpler models do surprisingly better than the complex model. We also found that SentenceBERT provides excellent representation which improved the results for almost all of the classification models.
Detailed description of the research process and findings are available in the PDF report and presentation slides.
Dhanny Indrakusuma
Redoan Rahman
Patrick Sui