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聚焦發展  FOCUS


            三位一體精準醫療模式
            A TRINITARIAN MODEL FOR PRECISION MEDICINE




            “智能醫學計算實驗室”聚焦三大                 The Intelligent Medical Computing Laboratory focuses on
            方向:圖像時空異質性分析、多模                 three strategic directions: spatiotemporal heterogeneity
            態生物醫學數據融合,以及疾病進                 analysis of medical images, multimodal biomedical data
            展預測與預後,匯聚跨學科人才、                 integration, and disease progression prediction and prognosis.
            前沿技術與臨床需求,打造出集科                 By converging interdisciplinary talent, advanced technologies,
            研、教學與產業轉化於一體的創新                 and clinical needs, the lab has created an innovative platform
            平台。年內,澳理大智能醫學計算                 integrating research, education, and industry translation. Within
            實驗室發表多篇高水平論文,在國                 its first year, it published multiple high-impact papers and
            際賽事中嶄露鋒芒,成為推動澳門                 excelled in international competitions, emerging as a driving
            醫學人工智能發展的重要力量。                  force for medical AI development in Macao.
            實驗室的科研項目以明確的戰略導                 The laboratory’s research agenda is shaped by a clear
            向和技術前瞻性作佈局。在醫學影                 strategic vision and technological foresight. In medical imaging
            像智能分析方面,團隊專注於開發                 analysis, the team is developing advanced AI algorithms for
            高效 AI 算法,涵蓋 CT、MRI 及超聲          automated annotation, lesion detection, and image quality
            掃描的自動標注、病變檢測和質量                 enhancement across CT, MRI, and ultrasound scans. For
            增強。在疾病預測模型方面,實驗                 disease prediction, the lab is pioneering multimodal data fusion,
            室致力於多模態數據融合技術的創                 integrating imaging, genomics, and electronic health records
            新應用,通過整合影像學、基因組                 to enable risk stratification and early warning. In AI-assisted
            學和電子健康記錄等異構數據,實                 clinical systems, significant breakthroughs have been achieved
            現疾病風險分層和早期預警。在 AI               in personalised interventions, leveraging real-world evidence
            輔助診療系統方面,實驗室基於數                 and clinical indicators to design tailored prevention, treatment,
            據和知識驅動的個性化干預研究取                 and rehabilitation plans.
            得重要突破。通過整合真實世界證
            據和臨床指標數據,量身定制預防、
            治療和康復方案。










































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