AI-Powered Tools in SLR: Systematic reviews are vital in consolidating research findings for informed decision making, policy-makers, clinical guidelines, and best practices. However, if you’ve ever undertaken one, you know the process is anything but straightforward.
From screening thousands of articles to managing complex data, a systematic review can take months or even years to complete.
In fact, studies show that an average systematic review requires around 1,139 hours of work—over 47 days of full-time effort!
Fortunately, AI-powered tools in SLR are stepping in to lighten the load, making the process faster, more accurate, and, dare we say, a little less daunting. Let’s dive into the biggest challenges researchers face in systematic reviews and how AI can help you overcome them.
1. Challenge: Time-Consuming Screening Process
Did you know? Screening citations is often the most time-consuming stage in systematic reviews, with researchers spending weeks sifting through thousands of studies to find relevant ones.
Manual screening is a slog. Studies estimate that reviewing just one article takes about 90 seconds—multiply that by thousands, and you’re looking at a monumental task.
How AI Helps – AccuScreener
- Faster Screening: AccuScreener can process up to 20,000 citations in a single day. That’s a staggering speed-up compared to traditional methods.
- Smart Filtering: By automatically flagging relevant studies and ranking them by importance, AccuScreener cuts down on irrelevant data and helps you zero in on key research faster.
2. Challenge: Building Complex Search Strategies
Fact Check: Studies have found that up to 30% of relevant studies may be missed in manual searches due to suboptimal search strategies.
Creating comprehensive search strategies, especially for databases like PubMed, isn’t easy. You need to know the right keywords, Boolean operators, and Medical Subject Headings (MeSH) terms, and even then, there’s no guarantee you’ll catch every relevant study.
How AI Helps – AccuSearch
- Automated Search String Generation: AccuSearch builds complex search strings for you, integrating Boolean logic and MeSH terms so that you get a broader, more inclusive result.
- Real-Time Feedback: AccuSearch’s “Get Hits” function shows you the number of articles retrieved instantly, allowing you to tweak your search as needed.
- Reduced Oversight Risk: The AI’s use of synonyms and related terms helps ensure you capture studies you might have missed.
3. Challenge: Managing Human Bias in Study Selection
Human bias is a well-documented issue in research. A study by The Cochrane Collaboration found that selective inclusion can skew findings by up to 45%.
When humans make subjective decisions about which studies to include, the risk of unintentional bias creeps in. These biases can alter the final outcomes, whether subconscious leanings or honest mistakes.
How AI Helps – RoB Master
- Objective Assessment: RoB Master automates risk-of-bias evaluations, using frameworks like Cochrane and JBI to provide an unbiased, standardized analysis.
- Enhanced Accuracy: The tool has shown up to 96.6% accuracy in risk assessment, minimizing human error.
- Multiple Frameworks: RoB Master supports a range of popular frameworks (Cochrane, NICE, and more), so you can tailor assessments to fit your review.
4. Challenge: Identifying correct evidences
Systematic reviews often process thousands of references. Managing this huge number manually could be error-prone.
Imagine juggling hundreds of studies, each packed with potential keywords, and then having to manually sort, label, and highlight relevant terms. The mental strain alone can be exhausting.
How AI-Powered Tools in SLR Helps – SYMPRO
- Keyword Highlighting and Scoring: SYMPRO highlights critical keywords and assigns scores based on relevance, making it easier to prioritize references.
- Efficient Data Management: The tool’s batch screening feature lets you exclude irrelevant articles quickly, saving you hours of work.
- Real-Time Collaboration: SYMPRO allows teams to work together in real time, making it ideal for large, multi-researcher projects.
5. Challenge: Inconsistent Abbreviations Across Documents
Reality Check: Misinterpretation due to inconsistent abbreviations is more common than you might think, especially in fields with heavy jargon like healthcare or legal research.
In large reviews, abbreviation consistency is crucial. Inconsistent abbreviations can lead to misunderstandings or make findings harder to follow across documents.
How AI Helps – AQUA
- Automated Abbreviation Standardization: AQUA scans your entire document (e.g., report, summary tables, or slide deck) and standardizes abbreviations, ensuring consistency.
- Context-Sensitive Precision: The tool is context-aware, so it applies industry-specific abbreviations intelligently, avoiding common errors.
- Flexible Formats: AQUA works with Word and PDF files, providing output that’s easy to integrate into your review.
6. Challenge: Ensuring Quality and Consistency in Data Extraction
Fact: Data extraction is one of the most error-prone stages in a systematic review, with up to 30% of extracted data containing errors according to research.
Even with diligent effort, extracting data manually introduces the risk of mistakes, especially with large data sets. Such errors can compromise the integrity of your review.
How AI Helps – AccuAI Suite
- Quality Checks: AccuAI’s tools provide discrepancy alerts, flagging inconsistencies and helping you correct them before they affect your results.
- Automated Highlighting: Tools like AccuScreener and SYMPRO highlight relevant data points, making it easier to extract data accurately.
- Standardized Outputs: With AI handling the bulk of data extraction, you get standardized outputs that ensure quality and reliability.
With AI doing the heavy lifting, you can achieve cleaner, more accurate data extraction and reduce the risk of errors in your final analysis.
Get access to all the AI-Powered Tools in SLR here!
7. Challenge: Staying on Track with Deadlines
The Reality: The screening step in systematic reviews may take several weeks to complete, and meeting deadlines is challenging, especially with multi-member teams.
Keeping track of project timelines, milestones, and team member contributions can be overwhelming, especially when deadlines loom.
How AI Helps – SYMPRO’s Project Management Tools
- Real-Time Updates: SYMPRO provides live updates on team progress, making it easy to spot and address bottlenecks.
- Automated Notifications: You’ll get reminders for upcoming deadlines, helping you and your team stay on schedule.
- Progress Tracking: Monitor project timelines visually, making it easy to track team contributions and prevent delays.
AI-Powered Tools in SLR- Wrapping Up
Conducting a systematic review doesn’t have to be a time-draining, frustrating experience. With AccuAI’s suite of tools—AccuScreener, AccuSearch, RoB Master, SYMPRO, and AQUA—you can overcome the major hurdles, from citation screening to data management and bias assessment.
Ready to see how these AI-Powered Tools in SLR can transform your next systematic review? With AI by your side, you’ll be able to focus on what matters most: producing high-quality, reliable research without the usual headaches.
Dive into the world of AI-powered research with AccuAI and elevate the way you conduct systematic reviews.