# Springbuilt

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Placement:** Finalist
- **Team:** [Shereen Lee](https://cerebralvalley.ai/u/springbuilt)
- **GitHub:** https://reversely-provinans.hf.space/worklist?tour=full
- **Demo video:** https://drive.google.com/drive/folders/1p39WaH9oIxIGSEc9ZzpcDExB6QKoL4Y2?usp=sharing
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/244

Hi! I built Provinans, a tool that helps research teams reconcile datasets for longitudinal studies. This week I focused on endometrial pathology in collaboration with Dr Blake Gilks, whose lab has conducted thousands of manual archive reviews over the years and sorely need this tool. Longitudinal cancer research can take up to 10 years to complete, leading to a severe bottleneck in the speed of cancer treatment. Using archival records to assemble cohorts can be a source of relief. But in a world where the shape of the data is constantly changing, it can be difficult to assemble a coherent cohort. 
In 2023, the  International Federation of Gynecology and Obstetrics changed their protocols in a way that completely changed how endometrial pathology is classified, adding new data fields, removing others, and changing requirements for what a “stage” of cancer means. This means that overnight, the classification which cancer stage patients were in changed overnight; one study estimates it’s up to 28%. Updates like this, in addition to the plain messiness of real-world data, like this severely bottleneck archives-based research.  Many leading labs around the world are still doing the process manually because there is so much complexity when it comes to joining patient records, and much of it requires a careful evaluation of context. But Claude Sonnet, equipped with careful harnessing, can be uniquely suited to deal with industry-specific standards, specifications, and highlighting the important judgment calls that researchers need to make. That’s why I found it so deeply important to create a traceable interface that helps data managers, annotators, and researchers alike grapple with assembling gold standard datasets that can assist a new wave of cancer research.

---

Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/244. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt