The PICOS framework for clinical questions with worked examples
How to turn a vague clinical query into a precise question by naming the population, intervention, comparator, outcomes and study design, with worked examples from several specialties.
Clinical evidence blog for clinicians and research teams
Practical guides to finding, reading and citing clinical evidence: how to frame a question, how to search trial registries well, how to weigh study designs and how to use AI without trusting it blindly.
Guides for evidence work that has to hold up
Every article is written for professionals who need to defend what they cite, whether in a clinical discussion, a medical information reply, a feasibility assessment or a value dossier. We explain the registries and databases we index, the methods behind good evidence questions and the limits of artificial intelligence in this field. When you are ready to apply it, see how ClinicalEvidence works or start with a focused clinical trial search.
All articles
Artificial intelligence in clinical trials and what it can and cannot verify
Where artificial intelligence genuinely helps across the trial lifecycle, from feasibility to evidence review, and which claims still need a human to check the source.
How to search ClinicalTrials.gov effectively
Practical search strategies for ClinicalTrials.gov, including condition and intervention fields, status and phase filters, and how to read a study record without missing posted results.
Levels of evidence explained from case reports to meta-analyses
A clear walk through the evidence hierarchy, what each level can and cannot tell you, and how to weigh studies of different designs when they disagree.
AACT database guide for clinical trial data teams
What the AACT database contains, how its tables map to ClinicalTrials.gov records, and when a data team should query it directly instead of using a search interface.
International Clinical Trials Registry Platform and EU CTR search guide
How to search the WHO International Clinical Trials Registry Platform and the EU Clinical Trials Register to find studies that never appear on ClinicalTrials.gov.
Why AI invents citations and how source verification prevents it
Why language models produce references that look real but do not exist, and how retrieval with automatic source verification keeps every cited sentence honest.
Trial landscape analysis before protocol design
How to map competing and completed trials, endpoints and enrolment patterns before you design a protocol, so your study answers a question the field still has open.
Topics we cover
- Framing clinical questions and search strategy
- Trial registries, including ClinicalTrials.gov, the EU Clinical Trials Register and the WHO ICTRP
- Evidence hierarchy and critical appraisal
- Clinical trial data for analytics teams
- Artificial intelligence, citations and source verification
- Trial landscape and feasibility work before protocol design
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Put the methods into practice with cited answers
Ask a clinical question and get an answer where every sentence links to an NCT number or PMID.