Leveraging Deep Semantic Embeddings and hierarchical clustering for identifying patient appointment scheduling issues
FALL 2022
A project originally used for the CS 230: Intro to Deep Learning final project. The project leveraged deep semantic embeddings and deep learning techniques. Full project code and dataset are private due to HIPAA regulation and patient confidentiality. Experiments included investigations into SBERT and various clustering algorithms.
Topics covered and tools used:
- SBERT
- Top2Vec
- GloVe
- NLTK
- PyTorch
- TSNE Plots
- Principal Component Analysis (PCA)