8/24 – 9/18

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 進行中 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

加入行事曆

選擇訂閱 Google Calendar,或下載通用的 ICS 檔案。

使用 Google Calendar 時,Google 會收到這份課表的公開連結。

Python機器學習在智慧醫療的應用

Python Machine Learning for Smart Healthcare

學期
113-1
學分
0 學分
當期課號
131212
永久課號
MDIH30001
開課單位
國際衛生碩士學位學程
授課教師
陳翎
校區
陽明
類別
必修
上課時間表
週四
7
15:30–16:20
Python機器學習在智慧醫療的應用
YS405(陽明)
2 節連堂
8
16:30–17:20

* 根據陽明交大上課時間表所列

概述

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.

先修科目

This course does not assume any programming experience, but previous programming experience will help.

備註

無備註

教學方式

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.

評分方式

In-class quiz 20% Assignment mid-progress presentation 30% Final assignment presentation 50%

課程大綱

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週次計畫
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 programming: numpy
第 5 週Numerical programming: pandas
第 6 週Introduction to Machine Learning and scikit-learn
第 7 週Python Machine Learning pipeline
第 8 週Mid-term assignment presentation
第 9 週Introduction to Deep Learning
第 10 週Clinical text processing: nltk
第 11 週Clinical text embeddings and gensim
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
第 17 週Additional materials
第 18 週Additional materials
教科書

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Office Hours
地點
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時間
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聯絡方式
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