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A Complete Guide to Using SciSpace for Biomedical Research

SciSpace AcademyEnglishLiterature reviewLiterature reviews for health and biomedical research

TL;DR

1-min read

This tutorial walks through a complete SciSpace workflow for biomedical literature, from the first search to a structured draft. It is aimed at biomedical and life sciences students, researchers and clinicians who run literature or systematic reviews and want to spend less time on reading, synthesis and drafting while keeping accuracy high.

Key takeaways

  • Searching for biomedical papers can be made faster without giving up relevance, so the review starts from a focused, useful set of studies rather than an unmanageable list of loosely related results.
  • PDFs can be read, summarised and queried directly in SciSpace, which helps you understand long clinical and laboratory papers quickly and locate the specific passages that answer your questions.
  • Core study details such as design, sample size, methods, outcomes and limitations can be extracted in a consistent way, and applying the same template to every paper makes later comparison far easier.
  • Comparing several studies side by side helps you identify shared themes, agreements and inconsistencies, which forms the backbone of a well-organised synthesis for a review.
  • Structured outlines and citation-supported writing help turn that synthesis into a clear academic draft, while you keep control of the argument and of how the evidence is interpreted.
  • Verifying AI output against the original papers is treated as essential, because summaries can miss subgroup results, adverse events or stated limitations that matter in clinical and scientific contexts.
Apply it

To apply this, run your next biomedical search in SciSpace, extract the same set of study details from each paper, and check every key number and citation against the source before drafting.

How to do it

  1. Search biomedical literature quickly

    Use SciSpace to search for biomedical literature faster while keeping results relevant. This is the first step in applying AI for biomedical research.

  2. Read and question research PDFs

    Open papers with Chat with PDF to read, summarise and ask questions. This helps you handle heavy reading loads efficiently.

  3. Extract core study details

    Pull out study design, sample size, outcomes, methods and limitations from each paper. Consistent extraction makes studies comparable.

  4. Compare studies and synthesise themes

    Compare several studies and synthesise their shared themes for your review. This reveals patterns across the evidence.

  5. Outline and write with citations

    Generate structured outlines and improve your academic writing with AI Writer and the citation generator. Citation support keeps your draft properly referenced.

  6. Verify every AI output

    Check AI outputs against the source papers to avoid inaccurate content. Accuracy is essential in scientific and clinical contexts.

Watch the tutorial33 min

AI for Biomedical Research: Search, Extract and Synthesise StudiesPlay video: AI for Biomedical Research: Search, Extract and Synthesise Studies

Chapters

  1. Welcome and agenda
  2. What is an AI research agent and how is it different from ChatGPT?
  3. Why SciSpace built a separate Biomedical Agent
  4. What can an AI biomedical agent do? CRISPR screens and literature review
  5. Flowcharts from SMILES strings and AI drug docking with AlphaFold
  6. How to write prompts for an AI research agent: do's and don'ts
  7. How to open the Biomedical Agent in SciSpace and upload files
  8. Can AI find FDA-approved drugs to repurpose for a disease?
  9. How the agent queries drug databases guided
  10. Why vague prompts give wrong answers, and ranking candidate drugs
  11. Biomedical literature review with AI: search strategy and research gaps
  12. Why ChatGPT forgets context in long chats and how research agents avoid it
  13. PRISMA flow diagram and summary tables in SciSpace outputs
  14. Where to find research gaps in the output (JSON and CSV)
  15. Generate scientific illustrations from your research with AI
  16. Designing a CRISPR screen with AI: genes regulating PD-1 expression
  17. Can you run AlphaFold protein folding inside an AI research agent?
  18. How the agent plans tasks, limits hallucinations and switches to the general agent

Try this on SciSpace

Frequently asked questions

What data should I extract from biomedical studies for a review?

Commonly extracted items include study design, population and sample size, interventions or exposures, comparators, outcomes and how they were measured, key results, and stated limitations. Using the same extraction template for every paper makes comparison easier and helps you judge the strength and consistency of the evidence.

Is it safe to rely on AI summaries of clinical papers?

AI summaries are useful for screening and orientation, but they can miss nuances such as subgroup results, adverse events or limitations. For anything that informs clinical decisions or published conclusions, confirm the details in the original paper, check numbers and citations, and apply your own critical appraisal of study quality.

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