Exciting to see BioClinical ModernBERT (base) ranked #2 among trending fill-mask models - right after BERT!
The large version is currently at #4.
Grateful for the interest, and can’t wait to see what projects people apply it to!
🚀Announcing BioClinical ModernBERT, a SOTA encoder for healthcare AI, developed by Thomas Sounack @tsounack for Dana-Farber Cancer Institute in collaboration with @Harvard, @LightOnIO, @MIT, @mcgillu, @AlbanyMed, @MSFTResearch.
Seamless continued pre-training enables SOTA…
You can just continue pre-train things ✨
Happy to announce the release of BioClinical ModernBERT, a ModernBERT model whose pre-training has been continued on medical data
The result: SOTA performance on various medical tasks with long context support and ModernBERT efficiency
You can just continue pre-train things ✨
Happy to announce the release of BioClinical ModernBERT, a ModernBERT model whose pre-training has been continued on medical data
The result: SOTA performance on various medical tasks with long context support and ModernBERT efficiency https://t.co/Wrs0gabWco
BioClinical ModernBERT is out!
Built on the largest, most diverse biomedical/clinical dataset to date
‼️Delivers SOTA across the board
Thrilled to be part of this effort led by @tsounack
BioClinical ModernBERT is out!
Built on the largest, most diverse biomedical/clinical dataset to date
‼️Delivers SOTA across the board
Thrilled to be part of this effort led by @tsounack
Hypoactive delirium—characterized by withdrawal, lethargy, and decreased responsiveness—is missed up to 75% of the time. Why? Because these patients don't "cause trouble."
They lie quietly, often dismissed as "just tired" or "a bit down."
These are the patients we're failing…
An open-source LLM performed comparably to GPT-4 in generating differential diagnoses for complex cases, indicating that high-performing, locally-deployable custom models can enhance clinical decision support while ensuring data privacy and flexibility. ja.ma/4bGTyHx
9 months ago @Color partnered with @OpenAI and @UCSF to bring world-class cancer expertise to everyone.
To achieve this, we designed a novel architecture that safely integrates GenAI into clinical practice.
We call it a “Large Language Expert” (LLE). 🧵
🎉 We're thrilled to announce the general release of three de-identified, longitudinal EHR datasets from Stanford Medicine—now freely available for non-commercial research-use worldwide! 🚀
Read our HAI blog post for more details: hai.stanford.edu/news/advancing…
𝗗𝗮𝘁𝗮𝘀𝗲𝘁…
Original Article by T.-L. Liu et al.: Does AI-Powered Clinical Documentation Enhance Clinician Efficiency? A Longitudinal Study nejm.ai/4g92VS5#AIinMedicine
🚨 Can LLMs identify Goals of Care (GOC) in cancer care documentation?
💻 Our latest study shows GPT-4o excels at extracting Advance Care Planning (ACP) details from clinical notes! @JPSMjournal
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