Abstractive Summarization of Postoperative Data Using Machine Learning Techniques
I virtually worked at the Biomedical Artificial Intelligence Lab at Brown University. Under the supervision of my PI Dr. Carsten Eickhoff, I conducted a project on computational methods to summarize electronic health records in order to aid doctors. The enormity of the records has raised concerns regarding storage overload and the impact on how clinical professionals use them; it is important to organize these notes. Using SQL and Python, I placed parameters on the dataset in preparation for running machine learning models. The BERT model has shown positive results in effectively summarizing the notes, and we are currently running other machine learning models to validate our results and make an impact in the biomedical field.
Lab work will seem daunting at first, but with the right amount of preparation and enthusiasm, it can be a rewarding experience. Meghna Chityala ’21