2 項進行中

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 進行中 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
111-1
學分
0 學分
當期課號
131207
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
選修
上課時間表
週二
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

9/13
第 2 週

Getting started with Python programming tools

9/20
第 3 週

Python programming: basics

9/27
第 4 週

Python programming: class

10/4
第 5 週

Python programming: debugging

10/11
第 6 週

Scientific computing: numpy

10/18
第 7 週

Clinical text processing: nltk

10/25
第 8 週

Medical image processing: OpenCV

10/25
第 9 週

Mid-term assignment presentation

11/8
第 10 週

Python Machine Learning: scikit-learn

11/15
第 11 週

Python Machine Learning pipeline

11/22
第 12 週

Clinical text embeddings: gensim

11/29
第 13 週

Introduction to Deep Learning

12/6
第 14 週

Python Deep Learning: Keras framework

12/13
第 15 週

Python Deep Learning: Keras simple classification model

12/20
第 16 週

Python Deep Learning: Keras pretrained models

12/27
第 17 週

Final assignment presentation

1/3
第 18 週

Q&A and further discussion

1/10
教科書

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Office Hours
地點
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時間
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