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dccastr0.bsky.social
Daniel Coelho de Castro
@dccastr0.bsky.social
240 followers 130 following 1 posts
Researcher in ML for health at @msftresearch.bsky.social. PhD alumnus Imperial College. He/him
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Reposted by Daniel Coelho de Castro
hylandsl.bsky.social
Stephanie Hyland @hylandsl.bsky.social · Jul 18
New work from my team! arxiv.org/abs/2507.12950
Intersecting mechanistic interpretability and health AI 😎

We trained and interpreted sparse autoencoders on MAIRA-2, our radiology MLLM. We found a range of human-interpretable radiology reporting concepts, but also many uninterpretable SAE features.
Insights into a radiology-specialised multimodal large language model with sparse autoencoders
Interpretability can improve the safety, transparency and trust of AI models, which is especially important in healthcare applications where decisions often carry significant consequences. Mechanistic...
arxiv.org
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Reposted by Daniel Coelho de Castro
ai.nejm.org
NEJM AI @ai.nejm.org · Jul 10
Datasets, Benchmarks, and Protocols by D.C. de Castro et al.: PadChest-GR: A Bilingual Chest X-Ray Dataset for Grounded Radiology Report Generation nejm.ai/44rk1a1

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Figure 1. Example of a Grounded Report from PadChest-GR. Figure 2. Illustration of the Data-Curation Pipeline. Figure 3. Screenshots of the Interface for Both Manual Annotation Stages.
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Reposted by Daniel Coelho de Castro
ai.nejm.org
NEJM AI @ai.nejm.org · Jul 3
A novel dataset designed to train and evaluate grounded report generation models from chest x-ray images includes comprehensive sentence-level bounding-box annotations for all clinically relevant findings in each image. Learn more: nejm.ai/44rk1a1

@dccastr0.bsky.social #AI #MedSky #MLSky
Figure 1. Example of a Grounded Report from PadChest-GR.
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dccastr0.bsky.social
Daniel Coelho de Castro @dccastr0.bsky.social · Jun 26
📣 Our new PadChest-GR benchmark in collaboration with @ua.es and MedBravo is published in @ai.nejm.org: ai.nejm.org/doi/full/10....!
📰 Also check out our blog post for why we're so excited about it: www.microsoft.com/en-us/resear...
💾 The dataset can be downloaded here: bimcv.cipf.es/bimcv-projec...
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