New AI test predicts heart disease years in advance

新型人工智慧檢測技術可提前數年預測心臟病風險

更新於: 2026年7月20日 上午01:30

Medical technology is undergoing a major transformation thanks to artificial intelligence.

醫療技術正在藉由人工智慧經歷重大變革。

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New AI-driven tools are now capable of predicting heart disease years before any clinical symptoms even appear, marking a crucial shift from reactive treatment to proactive, preventive care.

新型AI驅動的工具如今能夠在任何臨床症狀出現前數年便預測心臟疾病,標誌著從被動治療轉向主動預防性照護的關鍵轉變。

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First, AI can analyze routine cardiac CT scans to identify subtle changes in heart fat that signal inflammation.

首先,AI可分析常規心臟CT以識別心臟脂肪中預示發炎的微小變化。

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Second, the CardiOmicScore blood test measures thousands of proteins to predict cardiovascular risks up to 15 years in advance by reflecting a person's lifestyle and environment.

其次,CardiOmicScore血液檢測藉由反映個人的生活方式與環境,測量數千種蛋白質以預測長達15年的心血管疾病風險。

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By utilizing existing, non-invasive procedures like routine check-ups and simple blood tests, these AI tools make heart disease prevention more accessible than ever.

透過利用現有的、非侵入式程序,如例行檢查和簡單的血液測試,這些AI工具使心臟疾病預防變得比以往任何時候都更容易實現。

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As these technologies integrate into standard healthcare, the goal is to intervene early, potentially saving countless lives by treating health issues long before they become life-threatening emergencies.

隨著這些技術整合入標準健康照護,其目標是早期干預,透過在健康問題演變為危及生命的緊急狀況前給予治療,有望挽救無數生命。

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文章閱讀結束

你閱讀了 6 句重點內容。

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What is the primary goal of these new AI-driven heart disease tools?

正確答案

To shift from reactive treatment to proactive, preventive care

How does the AI analyze cardiac CT scans for heart disease?

正確答案

By identifying subtle textural changes in the fat surrounding the heart

What advantage does the CardiOmicScore blood test offer?

正確答案

It captures biological changes linked to lifestyle and environment

Why are retinal scans useful for assessing cardiovascular health?

正確答案

Because they allow direct observation of blood vessels without surgery

What is the role of AI tools in relation to medical professionals?

正確答案

They assist healthcare professionals by providing data-driven risk scores

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