RepresentHer

Equity Evaluation
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Inspiration

To combat the under-representation of Women's health in Clinical Trials

What it does

MVP pipeline that ingests Clinical Trials PDFs, extracts structured gender demographic and safety reporting fields with an LLM, verifies claims with an auditor agent, and scores each paper for equity.

How we built it

Stack: Python, Streamlit, Cursor, Grok, Pandas, VSCode

Challenges we ran into

Implementing our API key, finding an efficient layout to display our tabular data, and PDF parsing.

Accomplishments that we're proud of

We are proud of creating a tool that can identify gender disparities, which is the first step in closing the gaps. We are also proud of increasing the efficiency of evaluating research papers which will ultimately speed up the process of improving female patient outcomes. We have firsthand experienced the downsides of being a woman in healthcare so a solution like this really does mean a lot to us!

What we learned

We learned just how large the gender gap actually is in clinical trials. There are lots of published studies that have outcomes marketed towards a generalized group, but have a misrepresentation of women in their sample groups.

What's next for RepresentHer

We want to expand the amount of clinical trials that can be parsed and uploaded to the tool. And also improve the accuracy and refine the data extraction from the PDF's so this tool can actually be used by clinicians in real healthcare settings.