Revolutionizing Systematic Literature Reviews with AI: A Deep Dive into Elicit

Systematic literature reviews (SLRs) are crucial for evidence-based decision-making in various fields, from healthcare to engineering. However, the traditional SLR process is notoriously time-consuming and resource-intensive. Fortunately, artificial intelligence (AI) is emerging as a game-changer, offering tools like Elicit to automate and accelerate the review process. This article will explore how Elicit leverages generative AI to transform the landscape of systematic reviews and meta-analyses.

The Challenge of Traditional Systematic Reviews

Traditional systematic reviews come with several pain points:

• Extensive screening: Sifting through thousands of papers to identify relevant studies is a laborious task.
• Manual data extraction: Extracting key data points from individual studies and compiling them into a usable format often involves error-prone manual data entry.
• Time Constraints: The entire process can take months or even years, delaying critical insights. A study by Borah et al. (2017) found that the average systematic review takes five researchers 1.3 years to publish (Borah et al. 2017).

Elicit: Generative AI for Streamlining Systematic Reviews

Elicit is an AI-powered tool designed to alleviate these challenges. It automates key aspects of systematic reviews, including screening and data extraction, using advanced language models. By leveraging Elicit, researchers can significantly reduce the time and cost associated with conducting comprehensive reviews.

Key Features of Elicit

• AI-Powered Screening: Elicit boasts a high level of accuracy in identifying relevant papers. Studies have shown Elicit can correctly identify over 96% of relevant papers, outperforming human research assistants in some cases.
• Rapid Data Extraction: Users can extract data from papers for screening or meta-analysis. Elicit offers a selection of over 30 predefined fields, allowing researchers to customize data extraction.
• Integration with Research Workflows: Elicit is designed to complement existing research workflows and integrates with tools like Zotero.
• Inline Verification: Elicit allows users to view supporting quotes from the source paper, ensuring transparency and accuracy in AI-generated results.

How Elicit Works

1. Upload and Search: The researcher uploads a set of research papers or conducts a search across Elicit's database of over 125 million papers.
2. Automated Summarization: Elicit generates summaries of the papers, helping the reviewer quickly assess their relevance.
3. Data Extraction: The researcher defines the data fields of interest, and Elicit extracts the relevant information from the papers.
4. Synthesis and Analysis: Finally, the extracted data can be synthesized and analyzed to draw conclusions and identify gaps in the literature.

Pricing Plans

Elicit offers a range of pricing plans to suit different needs:

• Basic (Free): Ideal for casual exploration, offering unlimited search and limited data extraction capabilities.
• Plus ($10/month billed annually): Suited for deeper research, includes unlimited chat with full-text papers and increased data extraction limits.
• Pro ($42/month billed annually): Designed for systematic reviews, offering dedicated workflows and increased extraction limits.
• Team ($65/user/month billed annually): Enables collaboration, offering pooled data extraction limits and live-editing features.
• Enterprise: Offers customized solutions for larger organizations, including volume discounts, training, and custom workflow development.

Benefits of Using AI in Systematic Reviews

• Increased Efficiency: Automating screening and data extraction saves significant time. Elicit can be 50%-80% faster than hiring human research assistants.
• Reduced Costs: By automating labor-intensive tasks, AI can reduce the overall cost of conducting systematic reviews.
• Improved Accuracy: AI algorithms can minimize human error and ensure consistency in data extraction.
• Greater Impact: Faster systematic reviews enable more timely evidence-based decision-making, which leads to greater impact in various fields.

The Future of Systematic Reviews

AI-driven tools like Elicit represent the future of systematic reviews. By automating key tasks and enhancing efficiency, AI is empowering researchers to conduct more comprehensive and timely reviews, ultimately leading to better-informed decisions and advancements across various disciplines. As AI technology continues to evolve, we can expect even more sophisticated tools to emerge, further revolutionizing the way systematic reviews are conducted.