近年來人工智慧(artificial intelligence, AI)蓬勃發展，憑藉著機器學習的技術及結合大數據(big data)，可以部份取代人工醫療的判斷及操作，讓治療不但更為精準，且更有效率。延續個人化精準醫療，人工智慧的介入將更能提升醫療準確率以及個人化程度。目前人工智慧對國內醫療生態雖然尚未帶來直接衝擊，然而未來逐漸邁入人工智慧時代後，病人看病、醫生診斷乃至治療，都可能呈現與現在完全不同的全新樣貌。有鑒於此，本智慧醫療專題課程旨在先讓修課同學了解人工智慧對醫療產業的潛在衝擊，接著學習如何將理學院應用物理、化學、生命科學、應用數學系等專業領域知識(domain knowledge)導入並運用於智慧醫療產業中，其次配合理學院四系執行之「個人化精準醫藥的人工智慧轉譯」AI專案計畫，最後輔以校外AI產學專家邀請演講及相關智慧醫療產業參訪，以期達到培育未來智慧醫療相關產業種子專業人才的目的。Artificial intelligence (AI) has been booming in recent years. With the help of machine learning technology and big data, it can partially replace the judgment and operation of artificial medical treatment, making treatment not only more accurate, but also more efficient. . Continuing personalized precision medicine, the intervention of artificial intelligence will further improve medical accuracy and personalization. Although artificial intelligence has not yet had a direct impact on the domestic medical ecosystem, as we gradually enter the era of artificial intelligence in the future, patient care, doctor diagnosis and even treatment may all take on a completely new look. In view of this, this smart medical special course aims to first let students understand the potential impact of artificial intelligence on the medical industry, and then learn how to apply domain knowledge from the Department of Physics, Chemistry, Life Sciences, and Applied Mathematics in the School of Science. ) is introduced and applied in the smart medical industry. Secondly, it cooperates with the "Artificial Intelligence Translation of Personalized Precision Medicine" AI project implemented by the four departments of the School of Science. Finally, it is supplemented by invited speeches by external AI industry and academia experts and visits to related smart medical industries. , in order to achieve the purpose of cultivating seed professionals for future smart medical related industries.
期刊論文
journal article
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 出席率出席率 Attendance |
10 | |
| 期中考期中考 midterm exam |
30 | |
| 作業及心得報告作業及心得報告 Homework and experience reports |
20 |
