智慧醫療資料分析程式設計

Programming for Intelligent Medical Data

學期

114-2

學分

3 學分

當期課號

545462

永久課號

EEBM30038

開課單位

智慧醫電工程研究所

授課教師

羅畯義

校區

光復

類別

選修

上課時間表

節	週二
5 13:20–14:10	智慧醫療資料分析程式設計 EE117（光復） 3 節連堂
6 14:20–15:10
7 15:30–16:20

* 根據陽明交大上課時間表所列

概述

This course aims to help students with the ability to apply programming and artificial intelligence methods for intelligent medical data analysis. The course begins with programming fundamentals and gradually covers biomedical data preprocessing, medical image and signal processing, and introduces practical case studies in machine learning and AI for healthcare. Through lectures, hands-on exercises, and project presentations, students will master data processing workflows, algorithm applications, and research practices, ultimately developing the skills to independently analyze medical data and propose innovative solutions

先修科目

Basic programming concepts (experience with any programming language is helpful, but beginners can also quickly catch up). Fundamental mathematics and statistics knowledge (linear algebra, probability, and statistics). Background in medicine, life sciences, or engineering is advantageous for understanding applications

備註

無備註

教學方式

1. Attendance & Grading a) Attendance will be calculated proportionally and will contribute to the final grade. b) Online Synchronous Learning: This course supports online synchronous sessions. However, students must consult with and obtain prior approval from the instructor before they are permitted to attend the course online. c) Approved absences will be considered in grading; unapproved absences will directly affect the attendance score. 2. Leave of Absence Students must request leave through the official university system, in accordance with school regulations. 3. Hardware Requirements Students are required to bring their own laptops for the hands-on sessions.

評分方式

Class Participation and Discussion: 20% Assignments: 20% Midterm Project: 30% Final Project Report: 30%

課程大綱

教師未提供此項資料

週次計畫

週次	主題
第 1 週	Introductions 時數：[2026-02-24]羅畯義(3.00)
第 2 週	Python Basics: Structures & Logic 時數：[2026-03-03]羅畯義(3.00)
第 3 週	Python Packages I 時數：[2026-03-10]羅畯義(3.00)
第 4 週	Python Packages II 時數：[2026-03-17]羅畯義(3.00)
第 5 週	Statistics: Exploratory Data Analysis 時數：[2026-03-24]羅畯義(3.00)
第 6 週	Statistics: Biomedical Data and Preprocessing 時數：[2026-03-31]羅畯義(3.00)
第 7 週	Statistics: Data Analysis 時數：[2026-04-07]羅畯義(3.00)
第 8 週	Midterm Projects 時數：[2026-04-14]羅畯義(3.00)
第 9 週	Machine Learning: Classical Models 時數：[2026-04-21]羅畯義(3.00)
第 10 週	Deep Learning Fundamentals 時數：[2026-04-28]羅畯義(3.00)
第 11 週	Natural Language Processing 時數：[2026-05-05]羅畯義(3.00)
第 12 週	Computer Vision in Medicine I 時數：[2026-05-12]羅畯義(3.00)
第 13 週	Computer Vision in Medicine II 時數：[2026-05-19]羅畯義(3.00)
第 14 週	Student Presentation I 時數：[2026-05-26]羅畯義(3.00)
第 15 週	Student Presentation II 時數：[2026-06-02]羅畯義(3.00)
第 16 週	Course Summary & Future Trends 時數：[2026-06-09]羅畯義(3.00)

教科書

Hangout References: 1. Python for health data science: a hands-on introduction, online textbook 2. Healthcare Data Analytics, Reddy, Chandan K., Aggarwal, Charu C., CRC Press, 2020

Office Hours

地點: EF-655A
時間: Mon 10:00 - 12:00, Other appointment by email
聯絡方式: email