Workshops to Support European Protection Agency's Development of Human Health Assessments: Artificial Intelligence and Open Data Practices in Chemical Hazard Assessment
On the 25th and 26th of May, 2022, Evidence Prime participated in Workshops to Support EPA's (Environmental Protection Agency) Development of Human Health Assessments, which focused on Artificial Intelligence and Open Data Practices in Chemical Hazard Assessment. The workshops were organized by the National Academies of Sciences, Engineering, and Medicine.
Since the practical application of systematic review (SR) methods is labor-intensive and costly, advances in artificial intelligence might ease those constraints through semi-automation and acceleration of SR workflows.
During the workshop, several presentations, discussions, posters, and software tool demonstrations took place. We could widen our knowledge about the key practical hurdles for applying SR methods, especially concerning data extraction, and what computational tools have been used to address them. One of the presented tools was Dextr*, which we developed in cooperation with DNTP and ICF.
You can watch the presentation here:
Moreover, you can also watch the presentation and a short DEMO of our solution for the SR - Laser AI**, which focuses on the screening module, here:
At the end of the workshop, participants identified the strengths and limitations of applying AI solutions in SR. We could also explore critical opportunities for furthering the application of AI in chemical hazard assessment. We also had a chance to participate in a great networking session and connect with other experts in the field of AI and NLP in toxicology.
If you are interested in our products or collaboration, don't hesitate to contact us at laser@evidenceprime.com.
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You can find more information about the workshop here: www.nationalacademies.org/event/05-25-2022/workshops-to-support-epas-development-of-human-health-assessments-artificial-intelligence-and-open-data-practices-in-chemical-hazard-assessment.
*Dextr: This work was supported by the Intramural Research Program (Contract GS00Q14OADU417, Task Order HHSN273201600015U) at NIEHS, NIH. DNTP initiated and directed the project providing guidance on tool requirements to support data extraction for literature-analysis as well as the evaluation plan.
**Laser AI: This work is supported by the European Union under the European Regional Development Fund via the "LaSeR" project (a “Fast Track to Innovation” program by the Polish National Centre for Research and Development).