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Check out our latest blog post on evaluating the medical knowledge of open LLMs!

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UNLOCK NEW POSSIBILITIES IN MEDICAL AI RESEARCH

MEDARC AIMS TO BUILD A PUBLIC COMMUNITY FOR CONTRIBUTIONS AND DEVELOP FOUNDATION
MODELS FOR MEDICAL AI RESEARCH.

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OUR APPROACH



We are developing novel methods and tools to tackle the grand challenges in
medical AI. We believe MedARC's approach is needed as a catalyst for progress.
In a partnership with other researchers and medical professionals, we will
design and launch projects that create large scale AI models for medicine, build
interdisciplinary teams to address clinical needs, share models and datasets,
publish results, establish best practices for reproducibility and transparency,
build a public community for contributions and collaborations, guide public
policies around AI development in medicine.

About Us


FEATURED PROJECTS

Projects

Fine-tuning Stable Diffusion for Chest X-ray Generation


Multimodal models trained on large natural image-text pair datasets have
exhibited astounding abilities in generating high-quality images (see: DALL-E 2,
CLIP, and of course, Stable Diffusion). However, medical imaging data
fundamentally differs from natural images. The language used to capture relevant
details in medical data succinctly uses a different, narrow but semantically
rich, domain-specific vocabulary.

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OUR TEAM

Leading an organization to build a community of collaborative research, industry
and government leaders. We have been working with major players in medicine and
healthcare, building research teams to address clinical needs.

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TANISHQ MATHEW ABRAHAM

CHIEF EXECUTIVE OFFICER




JEREMY HOWARD

PRESIDENT




BIJOU ABRAHAM

CHIEF EXECUTIVE ADVISOR


WE ARE GRATEFUL FOR THE SUPPORT.

While MedARC is an independent research organization, we can pursue our open
approach to medical AI research through the support of our partners.

Click here to learn more about our partners and team.





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