Python機器學習在智慧醫療的應用
Python Machine Learning for Smart Healthcare
| 節 | 週五 |
|---|---|
7 15:30–16:20 | Python機器學習在智慧醫療的應用 YN511 2 節連堂 |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
透過人工智能的技術,來輔助醫療人員在臨床上做判讀、診斷、開藥、甚至是預警,已成為近年來醫院發展重點之一。人工智能的核心技術是「機器學習」。本課程的目標是給有興趣對機器學習一探究竟的醫學院學生們一個入門的管道:從基本的Python程式語言教起,透過醫療數據的實例,特別是影像數據與文字數據,以實作的方式帶領學生進入「機器學習」的世界,最後讓學生們進入「機器學習」中目前最熱門的領域「 深度學習」。 Artificial Intelligence has shown great success in a wide range of smart healthcare and public health applications, from diagnosis and prescription suggestions, patient monitoring, disease prediction, to pandemic spread prediction. The goal of this introductory course is to provide an entry point for students who are interested in applying AI to solving healthcare related problems. We will start from Python programming basics, proceed to Machine Learning using real-world healthcare data, including medical images and clinical notes, and then enter the world of Deep Learning, the hottest subfield of Machine Learning.
本課程不預設寫程式能力,但是有統計軟體程式或程式語言撰寫經驗會有幫助。
本課程的內容皆以Python程序語言實作,請學生自備筆記型電腦。測驗方式包含2-4次隨堂小測驗與學期作業。學期作業分二次報告,包含期中進度報告與期末報告。 The course is designed to be mainly a hands-on programming course accompanied with lectures explaining basic concepts, so students are required to bring their own laptops to class. The most basic laptop with WIFI capability will be sufficient, since we will be using an online programming platform. Course assessments include 2-4 in-class quizzes and a course assignment. There will be a mid-progress presentation and final presentation for the assignment.
隨堂練習20% 作業期中進度報告30% 作業期末報告50% In-class quiz 20% Assignment mid-progress presentation 30% Final assignment presentation 50%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to the course and Machine Learning |
| 第 2 週 | Python programming: basics |
| 第 3 週 | Python programming: class and debugging |
| 第 4 週 | Numerical computing: numpy |
| 第 5 週 | Numerical computing: pandas |
| 第 6 週 | Public holiday |
| 第 7 週 | Introduction to Machine Learning and scikit-learn |
| 第 8 週 | Public holiday |
| 第 9 週 | Python Machine Learning pipeline |
| 第 10 週 | Introduction to Deep Learning |
| 第 11 週 | Clinical text processing and embeddings |
| 第 12 週 | Medical image processing: OpenCV |
| 第 13 週 | Python Deep Learning: Keras framework |
| 第 14 週 | Python Deep Learning: Keras simple classification model |
| 第 15 週 | Python Deep Learning: Keras pretrained models |
| 第 16 週 | Final assignment presentation |