OpenMed's synthetic discharge demo rejects a false potassium claim

OpenMed, the open-source clinical NLP project created by Maziyar Panahi, withheld a draft discharge brief in a planted-error demonstration after a local natural language inference model found the brief contradicted the note it cited. The demo planted a false potassium claim in a synthetic note, and the pipeline returned no text rather than passing the contradiction to a human reviewer. The project positions the refusal-first behavior as a safeguard for discharge summaries, which carry lab values and treatment history into the next setting of care.

OpenMed's synthetic discharge demo rejects a false potassium claim Maziyar Panahi's OpenMed used a planted potassium error in a synthetic note to show a brief returning no text rather than passing a contradiction to review. By RuntimeWire Staff https://runtimewire.com/author/runtimewire-staff · Published Primary source: Aligned News — AI Intelligence https://x.com/OpenMed AI/status/2119422183692779529 Why it matters Discharge summaries carry lab values and treatment history into the next setting of care, so a generated brief that contradicts its own citation can mislead the next clinician. OpenMed's demo shows a local, open-source pipeline choosing refusal over a polished but wrong draft, while keeping final approval with a human reviewer. OpenMed https://github.com/maziyarpanahi/openmed?ref=runtimewire , the open-source clinical NLP project created by Maziyar Panahi https://maziyarpanahi.com/?ref=runtimewire , withheld a draft discharge brief in a planted-error demonstration after a local natural language inference model found that the brief contradicted the note it cited.… When you purchase through links in our articles, we may earn a small commission https://runtimewire.com/affiliate-monetization-standards . This doesn’t affect our editorial independence.