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AI for Education and Research
Examples of AI Tools
- Trip has an AI search tool that uses a LLM to produce answers to clinical questions from the Trip Medical Database. Responses will include citations that link through to articles and guidance. You can also search other clinical questions that have been previously asked. Log in using your NHS Athens account to access Trip Pro
- MS Copilot uses a LLM to answer questions in a conversational way. It will reference its sources which include: The internet, it’s own knowledge base and conversation history. Copilot can generate images using a text-to-image generator - however some, (such as anatomical), may not necessarily be accurate.
- AI for Research | Scite uses “Smart Citations” to analyse how scientific papers are cited—showing whether each citation supports, contrasts, or merely mentions a claim, helping researchers quickly assess the reliability and context of academic literature.
- Elicit: AI for scientific research is a little different and uses machine learning and natural language processing (NLP) to help you find relevant research papers. It will then summarise the paper and extract key information such as formulas or statistical tests.
- ResearchRabbit: AI Tool for Smarter, Faster Literature Reviews
- Consensus: AI for Research
- Connected Papers | Find and explore academic papers
- Semantic Scholar | AI-Powered Research Tool
- Litmaps | Your Literature Review Assistant
- Rayyan: AI-Powered Systematic Review Management Platform
- Paper Discovery - Find Relevant Academic Literature Using Citations | Inciteful
Read this UK Research Integrity Office (UKRIO) post on research integrity.
Be aware of copyright responsibilities.
Consider who owns the information or data you are using. Do not upload copyrighted materials to AI tools unless you have explicit permission to do so. Keep in mind the principles of copyright and generative AI, as well as the scope of the NHS CLA Licence. Check the publisher’s website for terms and conditions—such as Creative Commons permissions when an article is open access. Before reusing any AI‑generated content, also review the tool’s terms and conditions to understand who holds the copyright.
Critical appraisal of AI research
Evaluating research relating to AI-powered tools requires new assessment criteria beyond traditional software evaluation. Dijkstra, Greenhalgh, Mekki & Morley’s (2025) How to read a paper involving AI offers a structured, clinically oriented method for scrutinizing AI research. It expands traditional critical‑appraisal practice by adding considerations unique to AI—such as data provenance, model transparency, ethics, and safe implementation—supported by a practical set of ten guiding questions.