KatherLab / STAMP
Solid Tumor Associative Modeling in Pathology
Why this job: works in the areas we cover, but does not say which job it does
What it does
STAMP is an end‑to‑end, weakly‑supervised deep‑learning pipeline that helps discover and evaluate candidate image‑based biomarkers from gigapixel histopathology slides, no pixel‑level annotations required. Backed by a peer‑reviewed protocol and used in multi‑center studies across several tumor types, STAMP lets clinical researchers and machine‑learning engineers collaborate on reproducible computational‑pathology projects with a clear, structured workflow.
Get started
git clone https://github.com/KatherLab/STAMP.git
cd STAMP - Maintenance
- Active
- Last commit 2 months ago
- Stars
- 133
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- Linux
- From the latest release
- Latest version
- 2.5.0
- Released 7 months ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- 82% closed
- 10 still open
- Pull requests
- 90 merged
- 4 waiting
- Releases
- 14
- 2 in the last year
- No contributing guide
- No security policy
- No code of conduct
More: download files, languages, topics and project record
Languages
- Python 100%
Topics
- agents
- bioimage-analysis
- bioinformatics
- deep-learning
- digital-pathology
- heatmaps-visualization-tool
- histopathology
- mcp
- mcp-server
- pathology
- pathology-informatics
- research
Project record
- JobOther AI tools
- StatusListed
- Commits828
- Forks63
- Watching2
- Stars in 28 days+2
- CreatedSep 22, 2023
- First seen by usNov 7, 2026
- CheckedNov 7, 2026