AI助攻心臟病藥物研發新突破

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新研究揭示人工智能如何徹底改變心臟病藥物處方方式

根據最新研究，一種嶄新的人工智能（AI）工具有望加快尋找心臟病治療方法的步伐。

心血管疾病（CVD）是整個歐盟死亡及致殘的主要原因，每年約造成170萬人死亡，影響超過6200萬人，這是經濟合作與發展組織（OECD）統計的數據。

倫敦帝國學院的科學家們研發了一款名為CardioKG的人工智能工具，結合了數千名參與者的心臟影像資料與龐大的醫療數據庫，旨在識別與疾病相關的基因，從而更快地找到心臟病用藥。

這些數據來自英國生物庫（UK Biobank），涵蓋患有心房顫動、心力衰竭、心臟病發作等疾病的病人及健康志願者。研究人員表示，透過這套系統，他們能更準確預測哪些藥物可能對特定心臟疾病患者有效。

帝國學院醫學科學研究所計算心臟影像組的組長Declan O’Regan指出：「知識圖譜的優勢之一，是能整合基因、藥物與疾病的相關資訊。」他強調這種方法有助於推動個人化醫療，讓治療方案更貼合每個人的心臟功能狀況。

此外，這項技術未來亦可拓展至其他疾病的研究，包括腦部疾病及肥胖症等，利用醫學影像數據進行深入分析。

O’Regan補充：「將心臟影像納入知識圖譜，顯著提升了新基因和藥物的識別能力，令我們有更多機會發現新療法。」

研究中突出提及的藥物包括用於治療類風濕性關節炎的甲氨蝶呤（methotrexate）及一類糖尿病藥物「格列汀類」（gliptins）。AI模型建議甲氨蝶呤可能有助於心力衰竭患者，而格列汀類藥物則或對心房顫動患者有益。

分析同時指出，咖啡因可能對部分心房顫動患者具保護作用，但研究者強調這並不代表人們應隨意改變咖啡因攝取習慣。

該研究的首席作者、帝國學院數據科學研究員Khaled Rjoob表示：「我們將進一步擴展這個知識圖譜，打造一個動態且以病人為中心的框架，捕捉疾病的真實發展軌跡。」

他認為，這將為個人化治療和疾病發展預測開啟全新可能。

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評論與啟示

這項研究展示了人工智能與大數據結合醫學影像的強大潛力，為心臟病患者帶來更精準且個人化的治療方案。過去心臟病藥物的研發往往耗時且成本高昂，AI的介入不僅能加速藥物目標的發現，更能根據個體心臟功能差異，量身訂造治療方案，提升療效並減少副作用。

更重要的是，這種「知識圖譜」的應用跨越了傳統的基因與藥物研究，融合了疾病影像和臨床資料，真正實現了多維度的醫學分析。這不僅有助於心臟病，也為其他複雜疾病如腦部疾病、肥胖症等提供了新的研究思路。

然而，這類技術的普及仍面臨數據共享、隱私保護及臨床驗證等挑戰。如何在保護患者隱私的前提下，推動跨機構合作，是未來推廣的關鍵。

總括而言，CardioKG的誕生標誌著醫療AI研究的一大進步，未來若能廣泛應用，將可能改寫心臟病治療的遊戲規則，真正實現「精準醫療」的願景，這對香港及全球的心臟病患者都帶來希望。

以上文章由GPT 所翻譯及撰寫。而圖片則由GEMINI根據內容自動生成。

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