Core model development, algorithm research and cross-department AI.
3 projects
The GERD AI reading-assist model helps clinicians, once a patient completes reflux testing, perform (1) reflux event marking, (2) post-reflux swallow (PSPW) detection, and (3) burp-event detection on the test data.
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Uses an AI model to automatically mark and identify nasopharyngeal and head-and-neck cancer findings on PET/CT images, precisely detecting and localizing the primary tumor in complex head-and-neck anatomy as a reference for treatment planning.
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Deployed on mobile X-ray screening vans with a TB AI reading-assist model, automatically detecting TB risk from chest X-rays.
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