The gender gap in evidence is measurable. FemHealth measures it. Standard database search shows you what exists. FemHealth adds a layer of equity-aware metadata — participant balance, exclusion patterns, and bias signals — that lets you assess the representativeness of the evidence base at a glance.
Every search result in FemHealth includes structured equity metadata that standard databases bury in abstracts — or don't surface at all:
Women have been systematically excluded from clinical research for decades — often due to concerns about hormonal variability, liability, or reproductive age. This exclusion is well-documented. What is less documented is how pervasive it still is across current literature, and how difficult it is to detect without reading full methods sections.
FemHealth surfaces this signal at the result-card level, enabling rapid triage of evidence quality from a gender equity perspective.
Accuracy depends on abstract quality. When participant sex is explicitly reported in the abstract (common in RCTs and systematic reviews), extraction accuracy is high. For studies that don't report sex breakdown in the abstract, FemHealth shows "data unavailable" — itself an informative signal.
PubMed (NCBI E-utilities), Europe PMC (EMBL-EBI), and OpenAlex. Each returns 20–25 results per query; results are merged, deduplicated, and sorted by relevance. Traditional medicine databases (DHARA/AYUSH, AJOL) are available via opt-in filter.
Free during beta. No account required. Search now →