HONG KONG, Oct. 31, 2024 /PRNewswire/ -- In a groundbreaking initiative, The Hong Kong University of Science and Technology (HKUST) has unveiled four AI-driven models poised to transform the medical and healthcare fields. These AI models can assist both general and specialist medical practitioners in diagnosing and prognosing up to 30 types of cancers and diseases, with some achieving accuracy comparable to that of medical experts with five years of experience or more.
Supported by the University's new AI supercomputing facility, which offers robust computing power, these large AI models surpass many existing systems due to their foundation on extensive data sets and novel machine training strategies. ย Prof. CHEN Hao, Assistant Professor in the Department of Computer Science and Engineering and project lead, said that one model processed over 160 million images across 32 cancer types for pathologicalย diagnostic tasks.
The four models include:
Prof. Chen, also the Director of the Collaboration Center for Medical and Engineering Innovation, jointly established between HKUST and Union Hospital, Tongji Medical College of Huazhong University of Science and Technology,ย stated, "We hope our AI tools will serve as valuable assistants for doctors, improving diagnostics, personalizing treatment plans, and streamlining different tasks. Building on our success, we are developing a wide range of AI applications targeting various clinical tasks, particularly precision oncology and computer-assisted intervention, while continuously enhancing our models with more data and modalities. By collaborating closely with clinical partners, we aim to drive improvements in patient care over the long term."
As a leader in AI research, HKUST has made significant contributions to medicine, including an AI model predicting the prognosis of brain tumor patients, a highly accurate blood test for early detection of Alzheimer's disease and mild cognitive impairment, and a microscope aiding near real-time judgments in lung cancer surgery, sparing patients' unnecessary procedures.
Video: https://www.youtube.com/watch?v=AET5DOWHeHo
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SOURCE The Hong Kong University of Science and Technology
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