Summary of Rapid Biomedical Research Classification: the Pandemic Pact Advanced Categorisation Engine, by Omid Rohanian et al.
Rapid Biomedical Research Classification: The Pandemic PACT Advanced Categorisation Engine
by Omid Rohanian, Mohammadmahdi Nouriborji, Olena Seminog, Rodrigo Furst, Thomas Mendy, Shanthi Levanita, Zaharat Kadri-Alabi, Nusrat Jabin, Daniela Toale, Georgina Humphreys, Emilia Antonio, Adrian Bucher, Alice Norton, David A. Clifton
First submitted to arxiv on: 14 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The Pandemic PACT Advanced Categorisation Engine (PPACE) is a fine-tuned model designed to automatically classify research abstracts from funded biomedical projects according to WHO-aligned research priorities. This task is crucial for monitoring research trends and identifying gaps in global health preparedness and response. The approach builds on human-annotated projects, which are allocated one or more categories from a predefined list. A large language model generates `rationales’ explaining the reasoning behind these annotations. This augmented data, comprising expert annotations and rationales, is used to fine-tune a smaller, more efficient model. Developed as part of the Pandemic PACT project, PPACE supports informed decision-making by research funders, policymakers, and independent researchers. The evaluation shows that PPACE significantly outperforms its baselines. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary PPACE is a special kind of computer program that helps classify research papers into different categories. It’s like a super smart librarian who can quickly sort through lots of papers to help us see what people are studying and where there might be gaps in our understanding. The program uses human-annotated projects, which means that experts have already looked at the papers and given them labels. Then, the program generates explanations for why those papers were labeled a certain way. This helps make the program even better at classifying new papers. The goal is to help people making decisions about research funding and global health priorities. |
Keywords
» Artificial intelligence » Large language model
