生醫資料、訊號及影像的人工智慧
Artificial Intelligence for Biomedical Data, Signal, and Image
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 生醫資料、訊號及影像的人工智慧 YR101 2 節連堂 |
6 14:20–15:10 |
* 根據陽明交大上課時間表所列
The course is designed to provide students with a comprehensive understanding of machine learning and deep learning theories that are specifically tailored for practical applications. The course will delve into the realm of AI and its potential applications in healthcare and will feature case studies that demonstrate real-world applications such as infoepidemiology during and post-COVID era, the hearing smart medical system, which leverages AI algorithms to analyze patient data and provide personalized treatment plans based on their hearing loss. The course will also demonstrate how AI can be used to predict heart failure risk from hemodialysis data and how mass spectrometry-based proteomics can be used. By using medical data examples, the course will highlight the potential and limitations of these techniques and provide students with a deep understanding of how these techniques can be applied in real-world settings. The course will also explore real-world implementations that involve various data processing methods, model development, and optimization strategies, providing students with a hands-on approach to learning. Overall, the course is an excellent opportunity for students to gain a comprehensive understanding of AI and its potential healthcare applications and explore the latest developments in machine learning and deep learning theories tailored for practical applications.
• Basic concept of Python programming
This course has been designed to offer practical exposure to a range of cutting-edge machine-learning models and signal-processing techniques.
期中報告: 30% 期末專題: 40% 出席: 10% 作業: 20% Midterm Report: 30% Final Project: 40% Attendance: 10% Homework: 20%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Traditional statistics vs. AI |
| 第 2 週 | Preprocessing health big data for AI models |
| 第 3 週 | Mid-Fall Festival |
| 第 4 週 | Infoepidemiology: Insights from the internet Search Trends in the COVID-19 pandemic |
| 第 5 週 | Infoepidemiology: Impacts of Mental Health and Long-COVID Symptoms in the Post-COVID era |
| 第 6 週 | Transitioning from artificial neural networks (ANN) to convolutional neural networks (CNN) |
| 第 7 週 | Developing hearing smart medical system: from prototyping to aging hearing signal and public health |
| 第 8 週 | Mid-term report |
| 第 9 週 | Introduction to Mass Spectrometry-Based Proteomics |
| 第 10 週 | Traditional vs. customized CNN models |
| 第 11 週 | Transfer learning and development of models |
| 第 12 週 | Real-time Analysis of Massive Continuous Data from a Dialysis Machine Signal to Predict Heart Failure Risk with New AI Platform |
| 第 13 週 | Techniques for model evaluation and addressing imbalanced data |
| 第 14 週 | Radiomics feature analysis |
| 第 15 週 | Ensemble learning: Integration of image and clinical data |
| 第 16 週 | Final report presentation |
Teaching materials and appointment articles
- 地點
- 守仁樓數位醫學中心
- 時間
- Tuesday 12:00-13:00.
- 聯絡方式
- Email聯繫: cywu4@nycu.edu.tw Prof. Chun-Ying Wu