Deep Medicine [Chapter 4] 醫療 AI 深度學習跟你想的不一樣？

What this episode covers

以 AliveCor 案例為核心，探討 AI 尤其是深度學習在醫療領域的潛力與挑戰為何，成功關鍵可能不在演算法本身，而在於資料品質、臨床假設是否正確，以及醫療場域的獨特性。透過失敗經驗與技術突破，我們認識到醫療 AI 不只是技術問題，更是資料與臨床思維的融合。核心問題：「人工智慧（AI），特別是深度學習（Deep Learning），在醫療領域的應用和潛力，究竟與人們的想像有何不同？它真正的價值和挑戰是什麼？是否真的能改變醫療？如果可以，它該怎麼做？真正有效的做法跟我們一般人（或科技業）想像的有什麼不同？」 AI 在醫療中的成功並不容易，需要從資料本質、臨床背景、建模方式來全盤思考。深度學習能發現人類看不到的規律，但前提是正確地設計 Input/Output、保留資料原貌並持續反思假設。與其盲目相信 AI 是神，我們更需要深入理解 AI 的推理邏輯與其對醫療體系的改變方式。 -- Hosting provided by SoundOn

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This episode was published on April 21, 2025.

What is this episode about?

以 AliveCor 案例為核心，探討 AI 尤其是深度學習在醫療領域的潛力與挑戰為何，成功關鍵可能不在演算法本身，而在於資料品質、臨床假設是否正確，以及醫療場域的獨特性。透過失敗經驗與技術突破，我們認識到醫療 AI 不只是技術問題，更是資料與臨床思維的融合。核心問題：「人工智慧（AI），特別是深度學習（Deep...

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