Automated Paper Screening for Clinical Reviews Using Large Language Models

Published: 2 May 2023| Version 1 | DOI: 10.17632/np79tmhkh5.1
Eddie Guo,


This project is a tool that allows researchers to automate screening of titles and abstracts for clinical review papers en bloc. Given a csv file describing your dataset(s) and csv files of the titles and abstracts of the papers you want to screen, the tool will automatically generate a csv file of the papers that meet your criteria. The tool is powered by the GPT API.


Steps to reproduce

To use the tool, you will need to provide the following files: - Dataset information csv with the following columns: - 'Dataset Name' (str): name of dataset - 'Inclusion Criteria' (str): screening inclusion criteria - 'Exclusion Criteria' (str): screening exclusion criteria - Dataset(s) - The name of the csv must match the 'Dataset Name' in the dataset information csv - There must be a "title" and "abstract" column in each csv To run the tool, run the following command: ```bash python3 ``` Then, type your dataset information csv path in. The tool will output the results in a csv file in the `results` directory. For an example of how to use the tool, see analysis.ipynb.


University of Calgary, University of Toronto


Artificial Intelligence, Medical Informatics, Natural Language Processing, Screening, Systematic Review