Scientific papers automatic summarization and extraction of evidence-based lifestyle reccomendations (MSc Project)
- Author: Lorenzo Germini
- University: EPFL
- Program: MSc Life Sciences Engineering
- University Supervisor: Prof Jacques Fellay
- Industry Partner: Burgeon Labs
- Academic year: 2021/2022 (Due: August 12, 2022)
My master project explores the implementation of an automatic abstractive text summarization pipeline with deep learning tools to extract key-takeaways from full-text research articles in the biomedical literature by distilling more concise text versions. The developed system is able to handle the complex information contained in a long scientific document given in input and subsequently produces scientific summaries according to a selected level of conciseness into a detailed or one sentence long TL;DR summary version.
A working demo of the project built with Gradio is available at https://huggingface.co/spaces/Blaise-g/summarize-biomedical-papers-long-summary-or-tldr