Evidence Prime is a collaboration between McMaster University and a group of committed, experienced Polish IT professionals, and individuals with a wide range of competencies, talents and interest.
We connected forces to become the market leader in creating innovative IT solutions for evidence-based health care professionals.
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Title - Artificial Intelligence to expedite creation of plain language summaries
Session Details - S07 - Machine learning and artificial intelligence
Date - Friday, Sep 23, 2022
Presentation Time - 11:30 AM - 11:45 AM
Presenting Author - Mr. Artur Nowak
Background: Plain language summaries help understand recommendations by providing more accessible and easy-to-read statements. However, creating and keeping these summaries up to date is a time-consuming task.
Objective: Evaluate whether AI can be applied to help with writing plain language summaries.
Methods: We randomly sampled 500 recommendations in English from the GRADEpro database that provided either Subgroup or Implementation Considerations. We extracted the recommendation statement and this additional information into two separate fields. We generated plain language versions of both fields using an AI system we built based on the GPT-3 model. We assessed the results using the Flesch Reading Ease formula. Three reviewers (ES, EB, JB) then manually evaluated 40 results for readability and factuality.
Results: The plain language summaries were successfully generated for 444 recommendations. The mean Flesch Reading Ease score increased from 17.86 to 46.71 (mean difference: 28.85, CI: (26.69, 31.01)) for recommendations and from 40.38 to 56.34 (MD: 15.96, CI: (12.7, 19.22)) for additional information. During the qualitative assessment of 40 recommendations, 25 were rated as improved, including three assessed as much improved. 9 results were evaluated as having the same level of readability. The evaluators also noted the good factuality of the results, although in 4 cases, the generated summary was inconsistent with the original statement.
Discussion: AI has a great promise to help maintain plain language summaries, especially if used in an interactive way. Therefore, we started the integration of AI into GRADEpro, and we plan to report further results of this work.
Nowak A 1 , Borowiack E 1 , Sadowska E 1 , Brozek J 1,2
Evidence Prime creates innovative tools for EBHC. GRADEpro (over 100k users) is the world’s most popular healthcare guideline development tool. Laser AI is a groundbreaking systematic reviews system, based on the award-winning AI model and reinvented user experience, used already by US National Toxicology Program, and German IQWIG and GBA.
GRADE your evidence and improve your guideline development in health care
COVID19 Recommendations and Gateway to Contextualization
The COVID19 living catalogue of guidelines collects best available recommendations on COVID19 for clinical, public health and health policy. It allows decision-makers to identify relevant recommendations for their question of interest.
Evidence Prime adapted GRADEpro to meet the needs and requirements of the COVID19 Recommendations and Gateway to Contextualization project. GRADEpro is used to extract and hold data from numerous publications by a large team of extractors and reviewers. Data from GRADEpro is then directly exported to Recommendation Map portal. Evidence Prime team assists with technical advice and data export management as well as continuously updates GRADEpro and the portal in order to keep the best quality and accessibility of our services.
After the summer break, we would like to invite you to the new webinar hosted by Evidence Prime, which will take place on the 29th of September at 10:00 EDT!
This time, we will focus on the exciting topic of the living practice guidelines in health care, which are increasingly being used to ensure that recommendations are responsive to rapidly emerging evidence.
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