- Hyptertension
Dataset for an AI project to automate quality assessment of systematic reviews
Skills / interests: Risk of Bias assessment, PICO annotation, Data extraction
Methodological skills / interests: Bias
This project aims to build a dataset of 2,000 systematic reviews for the development of an artificial intelligence (AI) tool to assess the quality of systematic reviews. The tool when finished, will be open access and free to all users. It is called WISEST. The assessment of a minimum of 50 systematic reviews will grant you co-authorship in our publications. You will assess the systematic reviews with ROBIS and AMSTAR-2 tools.
Before appraising/assessing the reviews for the dataset, training on ROBIS and AMSTAR-2 will be provided, followed by piloting until the assessments of the reviews are consistent with the established decision rules. We have developed very specific instructions how how to assess the systematic reviews using these two tools. An expert methodologist will check your assessments and provide feedback, so that all assessments are standardised.
We will publish a methods study comparing the two tools, a dataset paper, and a final tool paper, which you will be a co-author (after completing 50 assessments).
I’m interested, how can I apply?
I’m Interested how can I participate?
Hello Carole, I am interested in helping you out. I have previous experience with systematic reviews and I am currently a science student at McGill in Montreal.
Hi Carole, I believe that the tool will be very useful to help those who are dedicated to Evidence-Based Medicine like me.
Hi! I have interest in collaborate with you. I am familiar with conducting systematic reviews, extracting datas and critical thinking skills. It would be great to be a part of this project.