#All python scripts and helper files that I wrote while doing research with Dr. Yufei Huang's Lab at UPMC Hillman Cancer Center
- Does not include code borrowed from other sources
- Outside code was adopted from Allen NLP and the DYGIE++ repo
- For the contrastive learning that was attempted the code from the SimCSE was adopted in order to run their supervised configuration with contrastive pairs including hard negatives
- To produce the hard negatives AMR graphs were used that were produced using the AMRLib package with SPACY
- To understand the details of how this code along with the other repos and packages were used the papers produced from this research will be included as PDFs some time soon
- For a quicker overview of the work performed powerpoint files will be included as well
- At a later date the materials used for the presentation at IEEE BHI 2023 will be added after October 18 2023
- The first will be a rougher version that was written as the final paper for my MS Project
- This draft is the longest and contains all of the details from the contrastive learning
- Also provides a lot of extra background on the subject area
- The second will be the 4 page paper that was submited to IEEE BHI 2023
- This paper contains the parts of the research that were more refined
- The extended abstract version that was accepted to IEEE BHI 2023 will be included as well
- This shortest 1 page version will be the best to read in order to get a grasp on the research without having to read a lot of detail
- As the research continues further updates will be made to this repo with more papers and code
- Currently working on experimenting with using Chat GPT and prompt engineering in order to perform the same MRM extraction
- Will soon be moving onto deploying these models to see what valuable insights can be retrieved when applying this method to a certain area of biomolecular research