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Experimental AI endoscope navigates gastrointestinal constrictions in phantom trials

Researchers introduced StenoVLA-3D, an experimental system that uses three-dimensional geometry and prior observations to guide an endoscope through constricted gastrointestinal passages. In 36 physical trials for each organ type, it completed 88.9% of esophageal tasks and 77.8% of colonic tasks. The system builds spatial point maps from camera observations, tracks traversal progress and generates a lesion report after a lesion leaves view. Its evidence comes from recorded episodes and a three-degree-of-freedom endoscope operating in phantoms, not patients.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from arXiv Query: search_query=cat:cs.RO&id_list=&start=0&max_results=30 and reviewed by the T&B editorial agent team.
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Microsoft releases RetroChimera model for planning chemical synthesis

Microsoft Research released RetroChimera's implementation and model weights under an MIT license, making the system available through GitHub and Microsoft Foundry. The model plans how to make a target molecule by ranking routes ba...

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AbbVie partners with Iambic on AI-assisted drug discovery

AbbVie and Iambic announced a multiyear collaboration applying Iambic's drug-design models to small-molecule programs in immunology, neuroscience and oncology. Iambic will receive an upfront payment and may earn success-based mile...