hce_nchu
115年
英文
第 38 題
📖 題組：
The integration of Artificial Intelligence (AI) into healthcare is no longer a futuristic concept but a rapidly unfolding reality. One of the most __36__ applications is in the field of diagnostic imaging. By training on millions of clinical images, AI algorithms can now identify patterns that are virtually __37__ to the human eye, leading to much earlier detection of life-threatening conditions. Beyond diagnostics, AI is significantly __38__ the pharmaceutical industry. Historically, drug discovery has been an __39__ endeavor, often taking over a decade and billions of dollars to bring a single medication to market. AI models can now predict how specific molecular structures will interact with biological targets, thereby __40__ the initial stages of research. This efficiency was particularly __41__ during the recent global efforts to develop vaccines at record speed. However, this technological shift is not without its __42__. As healthcare providers become increasingly dependent on automated systems, questions regarding data privacy and "algorithmic bias" have surfaced. If the data used to train AI is not diverse, the resulting tools may provide __43__ outcomes for certain demographic groups. Therefore, it is __44__ that developers and medical professionals work together to ensure these systems are both transparent and __45__. The goal remains a synergy between human empathy and machine precision.
The integration of Artificial Intelligence (AI) into healthcare is no longer a futuristic concept but a rapidly unfolding reality. One of the most __36__ applications is in the field of diagnostic imaging. By training on millions of clinical images, AI algorithms can now identify patterns that are virtually __37__ to the human eye, leading to much earlier detection of life-threatening conditions. Beyond diagnostics, AI is significantly __38__ the pharmaceutical industry. Historically, drug discovery has been an __39__ endeavor, often taking over a decade and billions of dollars to bring a single medication to market. AI models can now predict how specific molecular structures will interact with biological targets, thereby __40__ the initial stages of research. This efficiency was particularly __41__ during the recent global efforts to develop vaccines at record speed. However, this technological shift is not without its __42__. As healthcare providers become increasingly dependent on automated systems, questions regarding data privacy and "algorithmic bias" have surfaced. If the data used to train AI is not diverse, the resulting tools may provide __43__ outcomes for certain demographic groups. Therefore, it is __44__ that developers and medical professionals work together to ensure these systems are both transparent and __45__. The goal remains a synergy between human empathy and machine precision.
- A revolutionizing
- B diminishing
- C mimicking
- D pardoning
思路引導 VIP
請觀察文章中對「過去」與「現在」製藥過程的描述：過去需要耗費十年與數十億美元，而現在 AI 能快速預測並加速研發。如果一個新工具能讓原本極度困難且緩慢的過程變得極其高效，我們會說這個工具對該產業造成了什麼樣規模的「變動」？
🤖
AI 詳解
AI 專屬家教
太棒了！你能精確捕捉到上下文的語氣並選出 revolutionizing，顯示出你對文章脈絡有很敏銳的觀察力，這正是閱讀測驗中最重要的「語感」與「邏輯分析」能力。
產業變革的動態描述
這題的核心在於理解 AI 對製藥產業帶來的「巨大影響」。文中提到，傳統藥物研發（drug discovery）既耗時又耗資，但現在 AI 能夠預測分子結構與生物標靶的互動，大幅提升了研發效率。這種從根本上改變產業運作模式、帶來翻天覆地進步的過程，用「革命性的改變」（revolutionizing）來形容最為貼切。相較之下，選項 (B) 減少、(C) 模仿或 (D) 寬恕，都無法精準對應文中描述的高效率與技術突破。
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