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Cyril Zakka, MD

@cyrilzakka6,701 subscribers

CEO @Almanac_Health. Prev: @Stanford @Huggingface

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Thrilled to release SmolVLM-2, our newest model, which runs entirely on-device and in realtime, offering a strong foundation for healthcare applications. 🤗🔥 With proper domain-specific training, small models enable offline inference of 2D (ECGs, CXRs) and even 3D modalities (CT, MRI) while remaining HIPAA-compliant by design. 🔒 VLMs have come a long way this year and we're excited to share our SoTA solution.

Thrilled to release SmolVLM-2, our newest model, which runs entirely on-device and in realtime, offering a strong foundation for healthcare applications. 🤗🔥 With proper domain-specific training, small models enable offline inference of 2D (ECGs, CXRs) and even 3D modalities (CT, MRI) while remaining HIPAA-compliant by design. 🔒 VLMs have come a long way this year and we're excited to share our SoTA solution.

46,435 görüntüleme

Christmas came early! 🎅🏻 Today marks the newest release of the HuggingChat 🤗 update with some really exciting capabilities! First up, automatic context injection! 1) Open a file in a supported app, summon HFChat, and it pre-populates the context window. No more copy-pasting

Christmas came early! 🎅🏻 Today marks the newest release of the HuggingChat 🤗 update with some really exciting capabilities! First up, automatic context injection! 1) Open a file in a supported app, summon HFChat, and it pre-populates the context window. No more copy-pasting

23,986 görüntüleme

The newest version of our Almanac preprint is out, and just in time for our demo at the Stanford AIMI Symposium 2023! Almanac is a retrieval-augmented LLM that provides up-to-date and verifiable answers to medical queries. Link: We benchmark our approach on a novel dataset of clinical scenarios (n = 130) evaluated by a panel of 5 board-certified & resident physicians, and demonstrate significant increases in factuality (mean of 18% at p-value < 0.05) across all specialties. More interestingly, because the retrieved data acts as a single source of truth, we find retrieval-based LLMs to be more robust to prompt injection and manipulation! Future work will involve expanding the scope of our dataset to more specialties and multimodal settings. #Medtwitter #MedEd

The newest version of our Almanac preprint is out, and just in time for our demo at the Stanford AIMI Symposium 2023! Almanac is a retrieval-augmented LLM that provides up-to-date and verifiable answers to medical queries. Link: We benchmark our approach on a novel dataset of clinical scenarios (n = 130) evaluated by a panel of 5 board-certified & resident physicians, and demonstrate significant increases in factuality (mean of 18% at p-value < 0.05) across all specialties. More interestingly, because the retrieved data acts as a single source of truth, we find retrieval-based LLMs to be more robust to prompt injection and manipulation! Future work will involve expanding the scope of our dataset to more specialties and multimodal settings. #Medtwitter #MedEd

18,124 görüntüleme

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