Literature Review Resources for Science Professionals

Not all AI tools are created equal. Especially when it comes to literature reviews. Nuance AI Lab just dropped one of the most useful reports I’ve seen this year: A head-to-head benchmark of 20+ tools claiming to do Deep Research—you know, those “get a full lit review from a single prompt” types. They shortlisted the top 8 and put them through the same prompts, with blind expert reviews across: ✅ Prompt adherence ✅ Citation quality ✅ Writing clarity ✅ Speed ✅ Cost The key takeaway? No tool does it all. But the right combo can deliver fast, well-cited, high-quality outputs—if you know how to use them. Here’s the go-to stack: 🔍 Use Elicit or Scite to find credible, peer-reviewed sources ✍️ Use ChatGPT or Claude to synthesize and write clearly 👀 Always bring in human oversight (especially for nuance and logic) Huge thanks to Samuel Salzer, Yash Panjwani, and the Nuance Behavior team for setting a new standard in how we evaluate AI tools for real-world research. This report is generous, rigorous, and refreshingly honest. If you’re in research, behavioral science, or content strategy: Read this report. Bookmark it. Share it. And subscribe to their newsletter for more like it 💌

Are you using an AI-powered scientific literature search assistant? Google Scholar is for dinosaurs. Here's three tools to supercharge your literature searches and surface the highest quality and most relevant scientific papers fast: Elicit - (https://elicit.com/) this is my personal go-to. In their literature search tool, papers will be listed along with a one sentence summaries generated by AI. You can add columns to the results table such as the number of participants in the study and major limitations. RCTs are clearly marked. Elicit also has a new tool where you can upload PDFs to be summarized, and another tool that lists important concepts related to your query. All of these capabilities are powered by GPT-like large language models. Consensus (https://lnkd.in/e_muNAuz) - this tool is the product of a Boston-based startup. It is similar to Elicit but with a more colorful, snappy interface. Compared to Elicit it is oriented more towards the every day user rather than academic researchers (for instance health and fitness junkies). One of the stand-out features here is the "consensus meter" -- if you ask a Yes/No question, the app will create a Yes/No/Maybe bar chart showing the number of corresponding papers, effectively acting as an automated literature review tool. Again, RCTs and observational studies are clearly marked, and "stand-out" high quality studies are also highlighted. Consensus is probably the best tool for quick answers about medical questions like "does zinc help with sleep?". System Pro (https://about.system.com/) - this tool is similar to the above two. Their search tool is not as feature rich as the above two, but there are two unique features provided here. First, there is the "synthesize" feature which will write a custom detailed article to answer your query, complete with references. There is also a "concept mapping" feature that provides a graph of concepts you can explore. Both of these features are quite amazing, but as they are beta and under development I found they they may be slow (20-30 seconds to load) and not always work for every search.

🔍 Enhance Your Systematic Review with AI Tools! Conducting a systematic review can be a daunting task, but AI tools can make it much more manageable. Here are some great tools to consider: 1. Formulate Research Questions - [Elicit.org](https://elicit.org/): Helps brainstorm and refine research questions. - [OpenAI ChatGPT](https://chat.openai.com/): Generates diverse research questions and helps with search strategies. 2. Develop Search Strategies - [Xtrct](http://xtrct.app): Uses semantic search to enhance study selection. - [Thalia](https://lnkd.in/dBEX72j2): Disambiguates terms with multiple meanings for accurate searches. 3. Screening and Data Extraction - [Covidence](https://www.covidence.org/): Facilitates efficient screening and data extraction using machine learning. - [Rayyan.ai](https://www.rayyan.ai/): Helps automatically identify articles for exclusion based on set criteria. 4. Literature Review - [Research Rabbit App](https://lnkd.in/drmmgxZr): Suggests related papers based on your Zotero library. - [Scite.ai](https://scite.ai/): Finds citations related to GPT-generated responses to support your research. 5. Writing and Summarizing - [Jenni.ai](https://jenni.ai/): Offers writing prompts and suggestions to streamline the writing process. - [PaperDigest](https://lnkd.in/dCiV4n9h): Provides summaries of key research papers to save time. 6. Create Graphical Abstracts - [Graphical Abstract Maker](https://lnkd.in/dhQ3Anaz): Turns complex research into easy-to-understand visuals. 7. Assess Risk of Bias - [RobotReviewer](https://lnkd.in/dsBCDgwt): Automatically extracts data and assesses bias in RCTs. 8. Trace Citation Networks - [CitationChaser](https://lnkd.in/dyMXzTUr): Identifies relevant research by tracing citation networks. By incorporating these AI tools into your systematic review process, you can save time and improve the quality of your research. Remember to report all AI tools used to ensure transparency and replicability. Happy reviewing! 📈

Still Stuck on Your Literature Review? Here’s the step-by-step workflow that takes you from blank page to publication-ready (Save this post) ——————————————— 1. Define Your Research Question   ➠ Don’t start searching aimlessly. ➠ Get crystal clear on your hypothesis. ➠ Make it specific, measurable, and relevant. ➠ Let your question guide every search and selection. 2. Develop a Search Strategy ➠ List your keywords and phrases. ➠ Choose the right databases (PubMed, JSTOR, etc). ➠ Use Boolean operators (AND, OR, NOT) for laser focus. ➠ Document everything for reproducibility. 3. Conduct the Literature Search ➠ Go systematic: search, collect, and organize with tools like Zotero or EndNote. ➠ Download full texts for in-depth review. ➠ Keep a log—you’ll thank yourself later. 4. Screen & Select Relevant Studies ➠ Review titles & abstracts. ➠ Exclude anything off-topic—be ruthless! ➠ Use flowcharts (PRISMA style) to show your process. 5. Extract & Organize Data ➨ Build a data extraction form: author, year, methods, findings. ➨ Summarize & spot trends or gaps. ➨ Spreadsheets and qualitative software are your best friends. 6. Critically Appraise the Literature ➨ How strong is the evidence? ➨ Assess sample size, bias, strengths, and weaknesses. ➨ Compare across studies—don’t just accept, analyze. 7. Synthesize the Findings ➨Group by theme, method, or outcome. ➨ Create a story with your data—use charts and concept maps. ➨ Identify gaps & suggest next steps. 8. Write the Literature Review ➨ Start with a clear intro—set the stage. ➨ Organize by theme or time. ➨ Discuss how your findings fit (or challenge) existing knowledge. ➨ End by highlighting key takeaways and future directions. 9. Revise & Edit ➨ Polish for clarity and flow. ➨ Double-check citations. ➨ Get feedback—from peers, mentors, even AI tools! 10. Update Regularly ➨ Science never sleeps, neither should your review. ➨ Keep tracking new research and update as you go. ——————————————— Pro Tip: ➠ Tag a friend who needs this workflow. ➠ Save for your next project. ♻️ Repost #LiteratureReview #GradSchoolTips #AcademicWriting #ResearchWorkflow #PhDLife #LinkedInGrowth