Evidence Prime

🎉 Excited to share our latest publication in BMJ Evidence-Based Medicine: "Opportunities, challenges and risks of artificial intelligence for evidence synthesis", led by Dr. Waldemar Siemens and Joerg Meerpohl Our paper explores how AI, particularly large language models (LLMs), can revolutionize systematic reviews while highlighting important considerations for their responsible use. We examine, among others: ✨ Key opportunities in automating tasks like literature screening and data extraction ⚠️ Critical validation challenges facing LLM implementation 🎯 Important risks to consider, from over-reliance to environmental impact This work emerged from discussions at Cochrane Germany's third Methods Forum, which took place on June 14, 2024, in Freiburg, Germany. The paper aims to guide the evidence synthesis community in leveraging AI responsibly. Read the full paper here: https://lnkd.in/ezgcSpRG

The concept of GRADE-adolopment was initially published in 2017. Since then, it has been added to the Lexicon of Clinical Epidemiology and is now part of the national methodology in the Czech Republic. Overall, the time and resources saved using the GRADE-adolopment approach are clear and worthwhile learning for any research team. To learn more about GRADE-adolopment, watch our latest webinar on YouTube: @EvidencePrime

Adolopment is an approach to contextualization of guidelines that is defined as: "The need for dialogue and formal consideration of the best available local evidence and criteria for adoption, adaption, or de novo creation of recommendations from an existing, trustworthy, guideline." The word has recently been added to the Lexicon of Clinical Epidemiology, and the process aims to help research teams by reducing resource waste. To learn more about GRADE-adolopment, watch our latest webinar on YouTube: @EvidencePrime

If a recommendation is not adopted or adapted, research teams will need to create it from scratch, otherwise known as a de novo recommendation. Adolopment is the process of adopting, adapting, or creating a De Novo recommendation to provide evidence-based recommendations for the local context based on existing guidelines. To learn about the GRADE-adolopment approach, watch our latest webinar on YouTube: @EvidencePrime

When a recommendation is changed using the GRADE-adolopment approach because of contextual evidence, we call this an adapted recommendation. Adapting existing guidance saves time and money, as only a portion of evidence has to be collected and interpreted to issue a locally relevant recommendation. Watch our latest webinar with Dr Miloslav Klugar and is all about the GRADE-Adolopment approach and how to use the adolopment module on GRADEpro YouTube: @EvidencePrime

📝 "Register today" Don't miss this opportunity ! We are excited to invite you to join us for our upcoming webinar on Laser AI, AI-powered systematic literature reviews, on Wednesday 4th December, 2024  for an insightful webinar where we will delve into the capabilities of Laser AI and explore how it can revolutionize your research workflow.Bakhita Barbara MihesoKenya Medical Research Institute (KEMRI)CochraneEvidence PrimeKirsty WatsonEdna Wanjiku   👉 Who Should Attend?   Everyone interested in leveraging AI for efficient research    💥 Don't miss this opportunity to learn how Laser AI can empower you to efficiently conduct systematic reviews   🕗  Time: 2:00PM-3:00PM EAT   📍   Venue: Online    👩 Presenter: Kirsty Watson, Business Development Lead Evidence Prime   🎙 Moderator: Edna Wanjiku ICT Officer Kenya Medical Research Institute (KEMRI) / Web Content Administrator-Cochrane Kenya    💥Register now:   https://lnkd.in/d68-Mav7

Adolopment is an approach to contextualization of guidelines that is defined as: "The need for dialogue and formal consideration of the best available local evidence and criteria for adoption, adaption, or de novo creation of recommendations from an existing, trustworthy, guideline." Adolopment is a process created to help streamline efficiency and minimize resource waste when contextualizing guidelines. To learn more about GRADE-adolopment, watch our latest webinar with Dr Miloslav Klugar on YouTube: @EvidencePrime

We have exciting news to share! 🥳 Evidence Prime has been awarded a grant under the Polish Agency for Enterprise Development (PARP) SMART Path program, part of the European Funds for a Modern Economy (FENG) initiative. 🎉 Out of over 2,700 applications, we are proud to be among the top 8% of selected projects, securing funding to drive innovation, digital transformation, and international growth. With this grant, we aim to enhance our AI capabilities, expand automation, and improve accessibility. This will allow us to continue providing solutions like Laser AI, simplifying the systematic literature review process and advancing evidence-based healthcare decision-making. We’re excited for the future and looking forward to the next steps on this journey! 🚀 #Innovation #AI #GrantAward #SMARTPath #EvidenceBased https://lnkd.in/dCvGN_CW

🔥 Straight from #ISPOREurope to the online #DataScienceSummit2024

Our team at Evidence Prime is wrapping up #ISPOREurope in Barcelona. I will miss the picturesque sunrises, but even more the great atmosphere of the conference, and wonderful collaborators: current and future. Please feel free to send me a connection request if you would like to keep in touch on all things HEOR, and especially automation of literature reviews with #LaserAI.