hce_nchu
115年
英文
第 36 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 stagnant
- B prominent
- C trivial
- D obsolete
思路引導 VIP
請觀察這句話的前後文：作者提到 AI 正從「科幻概念」轉變為「迅速展開的現實」，且隨後詳細描述了它能處理數百萬張影像、找出人類肉眼看不見的特徵。在這種描述「強大技術突破」的語境下，你認為這個應用應該被形容為「微不足道的」、「過時的」，還是「非常顯著且重要的」呢？
🤖
AI 詳解
AI 專屬家教
太棒了！你能精準選出 prominent，代表你已經成功掌握了文章開篇的語境調性。這題的關鍵在於前文提到的「人工智慧已非虛幻概念，而是正在迅速展開的現實」。既然 AI 在醫療領域的發展如此蓬勃，那麼在影像診斷（diagnostic imaging）上的應用自然是極其「顯著且重要」的，這與文中提到的技術突破完全吻合。
語境線索與詞義辨析
從邏輯上看，其他選項如 (A) stagnant（停滯的）、(C) trivial（瑣碎的）與 (D) obsolete（過時的）都帶有負面或消極的意涵，與文章描述的「處理數百萬張臨床影像」這種強大功能完全背道而馳。這道題目具有很高的鑑別度，它不單純考驗單字量，更要求學生從「earlier detection of life-threatening conditions（早期發現致命疾病）」等描述中，感受到該技術的影響力，進而推論出正向且具代表性的形容詞。你能避開干擾項，展現了極佳的閱讀敏銳度！