Clinical Literature Triage with AI
Screen and summarise clinical research faster with AI, then appraise the evidence that matters yourself
A taste of a lesson
An AI summary says a new drug reduces heart attacks by 40%. Is that worth sharing with my team?
Not yet. First find the paper and check the figure. A 40% reduction is almost certainly relative. If the risk went from 5% to 3% over three years, that's a 2 percentage point absolute reduction, so 50 people treated to prevent one event. Then check: was it randomised, who was studied, was the outcome patient important, what were the confidence intervals and harms, and who funded it? What's the absolute risk in the control group of the study you have?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Frame clinical questions with PICO and turn them into search strategies
- Use AI to screen abstracts and extract study details with verification
- Detect fabricated references, overstated conclusions and misread statistics
- Apply critical appraisal basics to the studies that matter
- Document AI assisted literature methods transparently
Lesson plan
- 1 Framing the question Turn a clinical problem into a precise PICO question and search concepts. Start
- 2 Screening with AI assistance Use AI to prioritise abstracts while keeping screening decisions transparent. Start
- 3 Extraction and its errors Draft extraction tables with AI and verify every figure against the paper. Start
- 4 Reading AI summaries critically Spot overstated conclusions, missing limitations and fabricated sources. Start
- 5 Appraisal essentials Apply core appraisal questions to the studies driving your conclusion. Start
- 6 Documenting your method Record tools, prompts and checks so your work can be trusted and reproduced. Start
Try asking
About this tutor
For clinicians, pharmacists, researchers, guideline developers and clinical librarians who need to keep up with literature. Education only. We use AI to help frame questions with PICO, generate search ideas, screen titles and abstracts, extract study details, and draft summaries, then focus on the failure points: fabricated references, missed nuance, overstated conclusions, outdated or retracted studies and biased search results. You practise verifying claims against the full paper, applying critical appraisal basics, and documenting your method so others can trust it. It complements, never replaces, systematic review methods and librarian expertise.
Reviews
4.7
3 ratingsSample
- Ama S.Sample
Logging prompts and verification steps made our journal club summaries much more trustworthy. Excellent on fabricated references.
- Kenneth O.Sample
Rigorous and practical. As a pharmacist I appreciated the appraisal refresher. Less useful if you already run systematic reviews.
- Margarethe L.Sample
The extraction lesson exposed how often AI swaps relative and absolute risk. I now verify every number against the tables.
About the teacher
Nurse turned informatics lead teaching safe AI use in health, research, care and public service
9 tutors 428 lessons taught Sample
I trained and worked as a nurse, moved into clinical informatics, and later supported research teams, social care services and public bodies with data and digital projects. That path taught me how much paperwork stands between professionals and the people they serve, and how badly things go when a tool is trusted beyond its limits. I teach clinicians, administrators, researchers,...
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