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課程名稱 |
人工智慧與智慧醫療
Artificial Intelligence and Intelligent Medicine |
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開課學期 |
112-1 |
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授課對象 |
學程 智慧醫療學分學程 |
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授課教師 |
林 澤 |
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課號 |
CommE5064 |
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課程識別碼 |
942EU0780 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期三7,8,9(14:20~17:20) |
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上課地點 |
共103 |
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備註 |
本課程以英語授課。上課地點:共同103未來教室。智慧醫療學程所屬電資學院「數據領域」課程。
總人數上限：60人 |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
Artificial intelligence (AI) can be applied to a wide range of areas. Notably, the fast-growing intelligent medicine area has created tremendous business opportunities recently. It also creates an ideal environment for AI-Biomedical interdisciplinary specialists to make considerable contributions and significantly impact the world. Intelligent medicine aims to utilize state-of-the-art AI technologies for many medical applications such as accurate disease risk prediction and essential predictors selection, which are for early precise and efficient treatments. In this course, we will introduce the vast potential of intelligent medicine and help students advance their skills in this area, and motivate them to become AI-Biomedical interdisciplinary scientists.
In addition, in this course, we will introduce potential partners for future interdisciplinary collaboration to our students and provide opportunities for practical implementations through several carefully designed experiments, which shall demonstrate how to leverage real-world medical resources and related AI technologies. Meanwhile, we plan to arrange visits to prestigious companies and institutes and several seminars given by domain experts to further inspire and motivate our students. |
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課程目標 |
1. To polish skills for integration of programming, medical data analysis, and machine learning.
2. To train intelligent medicine specialists through practical implementations and connect them to potential future collaborators.
3. Promote the collaboration between the College of EECS and Medicine. |
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課程要求 |
Required pre-request：Machine Learning
Recommended pre-request: Python Programming for Intelligent Medicine (智慧醫療程式設計) or Special Topics in Innovative Integration of Medicine and EECS (醫學電資整合創意專題) |
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
Lectures will be based on lecture notes and slides and will be flipped classroom. |
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參考書目 |
1. “Machine Learning and AI for Healthcare: Big Data for ImprovedHealth Outcomes,” 2nd Edition, by Arjun Panesar.
2. “Artificial Intelligence in Healthcare: AI, Machine Learning, and Deepand Intelligent Medicine Simplified for Everyone,” by Dr. Parag SureshMahajan MD.
3. “Artificial Intelligence in Healthcare,” edited by Adam Bohr andKaveh Memarzadeh. |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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Week 1 |
9/6 |
Course announcement
Video record: AIIM-wk1-intro AI and IM (+ group discussion) |
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Week 2 |
9/13 |
Pre-class:
1. The rise of artificial intelligence in healthcare applications
2. Machine learning basics
3. DFN basics
In-class:
Group discussion (pre-class materials) |
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Week 3 |
9/20 |
Pre-class:
1. CNN Case study: DNN for NSCLC prognosis prediction (genetic data)
In-class:
Workshop: IDE construction and essential tools instruction |
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Week 4 |
9/27 |
Pre-class:
1. RNN
In-class:
Group discussion (pre-class materials) |
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Week 5 |
10/4 |
Pre-class:
Transformer-1
Transformer-2
In-class:
Group discussion (pre-class materials) |
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Week 6 |
10/11 |
In-class:
Workshop: Medical time series processing
Case study: RNN(DeepSTI)
Case study: RNN(X-RIM)
Case study: Transformer(TransEHR)
Case study: Transformer(MetaEHR) |
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Week 7 |
10/18 |
Domain expert talk and panel discussion |
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Week 8 |
10/25 |
Midterm presentation: Final project proposal |
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Week 9 |
11/1 |
In-class:
Workshop: Interpretability |
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Week 10 |
11/8 |
Pre-class:
Graph Neural Networks (GNN)
In-class:
Group discussion (pre-class materials)
Group discussion (for the final project) |
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Week 11 |
11/15 |
In-class:
Case study (James' EMBC'23 paper)
Case study (NG-DTA)
Group discussion (for the final project) |
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Week 12 |
11/22 |
Domain expert talk and panel discussion |
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Week 13 |
11/29 |
Midterm presentation: Paper survey |
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Week 14 |
12/6 |
No class
12/01(Fri.) 11:00-12:00am -- Healthcare Expo |
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Week 15 |
12/13 |
In-class:
Recent progress/trend of intelligent medicine (FL)
Group discussion (for the final project) |
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Week 16 |
12/20 |
Mini-workshop of final presentation
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