Harnessing AI for Efficient Systematic Reviews in Medical Publications

8:55 AM - 9:10 AM

In the era of evidence-based medicine, the integrity and efficiency of systematic reviews are paramount. Yet, the escalating volume of medical literature challenges this foundation, threatening the timeliness and accessibility of these vital reviews. This presentation proposes a forward-looking solution to these challenges: the integration of Artificial Intelligence (AI) in the systematic review process.

We explore how AI, particularly through Natural Language Processing (NLP) and machine learning, can streamline the identification, appraisal, extraction and synthesis of medical evidence. By automating these critical steps, AI promises to significantly reduce the labor and time traditionally required. This automation can contribute to human centric living systematic reviews, which are updated in real-time, ensuring that the latest evidence informs clinical and policy decisions without delay.

By attending this session, participants will gain insights into the potential of AI to address the current limitations of systematic reviews. The talk aims to inspire attendees to embrace AI technologies, paving the way for more efficient, accurate, and up-to-date evidence synthesis, supporting the rapid generation of reliable evidence for healthcare decision-making.