課程目標及內涵：智慧醫療入門
一、課程目標（Course Objectives）
了解人工智能在醫療領域的應用潛力：培養學生對人工智能在醫療應用的基本認識，並具備批判性思考能力，以因應未來醫療產業可能發生的變革。
掌握專業知識評估智慧醫療產業的方法：學習如何將理學院的核心專業知識，如應用物理、化學、生命科學及應用數學等，有效導入並評估智慧醫療產業的發展。
二、課程內涵（課程內容）
第一部分：人工智慧在醫療領域的應用潛力（第一部分：人工智慧在醫療領域的應用潛力）

發展趨勢（發展趨勢）：探討醫療領域的核心智慧的最新發展方向與未來展望。
應用案例（Application Cases）：分析AI在疾病診斷、藥物研發、健康管理、手術輔助等方面的實際應用案例。
倫理（Ethical Issues）：研究人工智慧醫療應用所涉及的資料隱私、算法偏見、責任歸屬等倫理考量與相關規範。
第二部分：將理學院專業領域知識導入智慧醫療產業（第二部分：將理學院專業知識引入智慧醫療產業）

應用物理（AppliedPhysics）：探索醫學影像技術（如MRI、CT）、放射治療、生物感測器等物理原理在智慧醫療的應用。
應用化學（Applied Chemistry）：研究藥物設計與合成、生物材料、體外診斷試劑開發等化學知識在智慧醫療的整合。
生命科學（生命科學）：連結基因體學、蛋白質體學、細胞治療等生命科學基礎，探討其在精準醫療與智慧健康方案中的角色。
應用數學（Applied Mathematics）：介紹資料分析、模型綜述、生物統計、演算開發等數學方法在醫療大數據處理與AI模型訓練的應用。

Course objectives and connotation: Introduction to smart medical care
1. Course Objectives
Understand the application potential of artificial intelligence in the medical field: Cultivate students' basic understanding of artificial intelligence in medical applications and develop critical thinking skills to cope with possible changes in the medical industry in the future.
Master the methods of professional knowledge to evaluate the smart medical industry: Learn how to effectively introduce and evaluate the development of the smart medical industry by incorporating the core professional knowledge of the School of Science, such as applied physics, chemistry, life sciences and applied mathematics.
2. Course connotation (course content)
Part One: The Application Potential of Artificial Intelligence in the Medical Field (Part One: The Application Potential of Artificial Intelligence in the Medical Field)

Development Trends (Development Trends): Explore the latest development directions and future prospects of core wisdom in the medical field.
Application Cases: Analyze practical application cases of AI in disease diagnosis, drug research and development, health management, surgical assistance, etc.
Ethical Issues: Research on ethical considerations and related norms such as data privacy, algorithm bias, and responsibility attribution involved in artificial intelligence medical applications.
Part 2: Introducing the professional knowledge of the School of Science into the smart medical industry (Part 2: Introducing the professional knowledge of the School of Science into the smart medical industry)

Applied Physics: Explore the application of physical principles such as medical imaging technology (such as MRI, CT), radiation therapy, and biological sensors in smart medical care.
Applied Chemistry: Research on the integration of chemical knowledge in smart medical care such as drug design and synthesis, biomaterials, and in vitro diagnostic reagent development.
Life Sciences (Life Sciences): Connect the basics of life sciences such as genomics, proteomics, and cell therapy to explore their role in precision medicine and smart health solutions.
Applied Mathematics: Introduces the application of mathematical methods such as data analysis, model review, biostatistics, and algorithm development in medical big data processing and AI model training.

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