Few rigorous studies of large language models have been done in cancer care. Off-the-shelf models developed on general patient populations may need significant tuning. https://t.co/yQUo9hNWiL
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
🧠 Long context (8192 tokens)
📚 Trained on 53.5B tokens, the largest biomedical + clinical corpus ever used for an encoder
📈 SOTA on biomedical and clinical tasks
⚡ Fastest inference & fine-tuning
🔓 Released in base & large sizes with training checkpoints
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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
Very excited to share the release of BioClinical ModernBERT!
Highlights:
- biggest and most diverse biomedical and clinical dataset for an encoder
- 8192 context
- fastest throughput with a variety of inputs
- sota results across several tasks
- base and large sizes
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Excited to be representing @danafarber at #ASCO25 to share our findings on "Using large language models to assess adherence to ASCO patient-oncologist communication standards"
Learn more at Poster #125 today at 1:30 pm!
A locally deployable, open-source LLM-Anonymizer can remove personal identifiers with high accuracy, offering a scalable and accessible solution for secure medical data processing. Learn more: https://t.co/XYkZNIVMl4
Feasibility Study for Using #LargeLanguageModels to Identify Goals-of-Care Documentation at Scale in Patients With Advanced Cancer: https://t.co/swsocaC3Ef
Authored by @lindvalllab et al.
Great work! Our lab is actively exploring how LLMs can enhance palliative care. We recently demonstrated that LLMs can capture ACP domains directly from the EHR
https://t.co/lCV3hLynWg
Read this week’s #EAPCblog by Charlotta Lindvall to find out more about AI and contributing to the upcoming special edition of Palliative Medicine on Digital Health in Palliative Care! https://t.co/lxwQ9CGA7j @lindvalllab@amaranwosu @COstgathe @cewalshe@PalliativeMedJ
Non-Hispanic white patients experience less asymmetry (73%) than other racial/ethnic groups (82%). Bridging this gap is essential #HealthEquity. #OncologyResearch@PECthejournal
https://t.co/qXBcS2LoyZ
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