Check out our newly published paper on Foundation Model for Advancing Healthcare in IEEE RMBE (IF=17.2).

Pls check out our Co-PAS system for diagnosing up to 12 knee abnormalities from mpMRI.

🚀 HKUST Smart Lab showcased our groundbreaking AI foundation models for healthcare, GSCo and mSTAR, to NVIDIA AI's Jensen Huang! Better things are on the way—learn more about these innovations above! #Healthcare #HKUST mSTAR: hkustsmartlab.github.io/2024/07/31/mst… GSCo: arxiv.org/abs/2404.15127

New study: Hierarchical Multi-Instance Learning (HMIL) for fine-grained WSI classification accepted by IEEE-TMI! 🎉 🔍 HMIL improves cancer diagnosis by leveraging hierarchical label correlations, outperforming SOTA methods on multiple datasets. More: hkustsmartlab.github.io/2024/12/27/hmi…

Check out our new IEEE TMI paper HMIL. HMIL improves cancer diagnosis by leveraging hierarchical label correlations, outperforming SOTA methods on multiple datasets.

Smart Lab unveils Smart-CCS! An AI system using pretraining & test-time adaptation for accurate cervical cancer screening. Validated on 20 retrospective & prospective datasets, it ensures high sensitivity & generalization in real-world settings. Read more: hkustsmartlab.github.io/2025/02/17/sma…

Our paper FOCUS is accepted at #CVPR2025! 🎉 FOCUS introduces knowledge-enhanced adaptive visual compression for few-shot WSI classification, leveraging foundation models & language priors to improve diagnostic accuracy. Read more: hkustsmartlab.github.io/2025/02/28/foc… #AI #Pathology #HKUST

Please check out our 2025 CVPR paper FOCUS on knowledge-enhanced adaptive visual compression for few-shot WSI classification.

Check out Smart-CCS! An AI system using pretraining & test-time adaptation for accurate cervical cancer screening. Validated on 20 retrospective & prospective datasets, it ensures high sensitivity & generalization in real-world settings.

🚀New paper alert! ➡️LLM 𝘄𝗶𝘁𝗵 𝗥𝗲𝗴𝗶𝗼𝗻-𝗴𝘂𝗶𝗱𝗲𝗱 𝗥𝗲𝗳𝗲𝗿𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗚𝗿𝗼𝘂𝗻𝗱𝗶𝗻𝗴 𝗳𝗼𝗿 𝗖𝗧 𝗥𝗲𝗽𝗼𝗿𝘁 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 The Reg2RG framework leverages segmentation masks to focus on diagnostic regions! Read the paper: 🔗ieeexplore.ieee.org/document/10963…

🎉 New in IEEE-TMI: Reg2RG from HKUST Smart Lab! A region-guided large language model that generates accurate, interpretable chest CT reports by linking diagnostic text to specific anatomical regions. More: smartlab.cse.ust.hk/2025/05/21/reg… #MedAI #Radiology #LLM

Excited our #mSTAR (Lead by YingxueXu & Yihui Wang) & #SmartPath AI for pathology are featured in nature! At #HKUST, we focus on real clinical impact & explainable #AIinMedicine. The journey’s just starting! Read: doi.org/10.1038/d41586… #DigitalPathology

We accept both 8-page-long papers and 4-page-long abstracts and welcome for the submission.

check out our new benchmark on genomic language models!

Meet SmartCare! 🚀 Developed by SmartLab (Lead by S. He and Y. Nie Yuxiang Nie) at HKUST. Now pilot-testing at the campus clinic with 15,000+ students & staff. Smarter triage, easier notes, better care. #AI #Healthcare Read more: smartlab.cse.ust.hk/2025/07/29/sma…