Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles.
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完成時間大約為12 小時
英語（English）
字幕：英語（English）
您將學到的內容有
Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.
Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.
Learn important approaches for leveraging data to train, validate, and test machine learning models.
Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 3 門課程（共 5 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為12 小時
英語（English）
字幕：英語（English）
提供方
斯坦福大学
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 2 小時
Why machine learning in healthcare?
完成時間為 2 小時
7 個視頻 （總計 34 分鐘）, 6 個閱讀材料, 3 個測驗
7 個視頻
History of AI in Medicine6分鐘
Course Overview4分鐘
Why Healthcare Needs Machine Learning2分鐘
Machine Learning Magic8分鐘
Machine Learning, Biostatistics, Programming4分鐘
Can Machine Learning Solve Everything?5分鐘
6 個閱讀材料
Getting Started: Creators of This Course5分鐘
Video Image Credit
Video Image Credit
Study Guide Module 15分鐘
Citations and Additional Readings10分鐘
Video Image Credit
3 個練習
Reflection Exercise15分鐘
Reflection Exercise10分鐘
Knowledge Check30分鐘
完成時間為 2 小時
Concepts and Principles of machine learning in healthcare part 1
完成時間為 2 小時
8 個視頻 （總計 51 分鐘）, 2 個閱讀材料, 3 個測驗
8 個視頻
Machine Learning Terms, Definitions, and Jargon Part 210分鐘
How Machines Learn Part 18分鐘
How Machines Learn Part 25分鐘
Supervised Machine Learning Approaches: Regression and the "No Free Lunch" Theorem3分鐘
Other Traditional Supervised Machine Learning Approaches3分鐘
Support Vector Machine (SVM)3分鐘
Unsupervised Machine Learning4分鐘
2 個閱讀材料
Study Guide Module 25分鐘
Citations and Additional Readings5分鐘
3 個練習
Reflection Exercise10分鐘
Reflection Exercise10分鐘
Knowledge Check30分鐘
完成時間為 2 小時
Concepts and Principles of machine learning in healthcare part 2
完成時間為 2 小時
10 個視頻 （總計 63 分鐘）, 3 個閱讀材料, 3 個測驗
10 個視頻
Deep Learning and Neural Networks6分鐘
Cross Entropy Loss3分鐘
Gradient Descent6分鐘
Representing Unstructured Image and Text Data5分鐘
Convolutional Neural Networks4分鐘
Natural Language Processing and Recurrent Neural Networks7分鐘
The Transformer Architecture for Sequences4分鐘
Commonly Used and Advanced Neural Network Architectures6分鐘
Advanced Computer Vision Tasks and Wrap-Up10分鐘
3 個閱讀材料
Video Image Credit
Study Guide Module 35分鐘
Citations and Additional Readings5分鐘
3 個練習
Reflection Exercise10分鐘
Reflection Exercise10分鐘
Knowledge Check30分鐘
完成時間為 2 小時
Evaluation and Metrics for machine learning in healthcare
完成時間為 2 小時
5 個視頻 （總計 35 分鐘）, 2 個閱讀材料, 3 個測驗
5 個視頻
Overfitting and Underfitting8分鐘
Strategies to Address Overfitting, Underfitting and Introduction to Regularization 5分鐘
Statistical Approaches to Model Evaluation5分鐘
Receiver Operator and Precision Recall Curves as Evaluation Metrics11分鐘
2 個閱讀材料
Study Guide Module 45分鐘
Citations and Additional Readings5分鐘
3 個練習
Reflection Exercise 110分鐘
Reflection Exercise 210分鐘
Knowledge Check30分鐘
審閱
來自FUNDAMENTALS OF MACHINE LEARNING FOR HEALTHCARE的熱門評論
由 AJ 提供2020年9月8日
Amazing course teaching the innumerous opportunities in the healthcare sector and the application of AI in the same. Beautifully drafted course with intriguing tutorials and exercises.
由 LS 提供2020年9月26日
Interesting and well crafted, it is mostly at an introductory level, but accurate and with many details regarding how to apply ML to healthcare. Worth to follow.
由 MM 提供2020年10月7日
An excellent course for professionals with healthcare background, specially for those who want to test the water before diving deep into AI in Healthcare.
由 SR 提供2020年10月9日
Outstanding teaching and pacing by both professors and an excellent generalized instruction of ML for healthcare.
關於 AI in Healthcare 專項課程
Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system -- such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.
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Is financial aid available?
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
Is this activity accredited for Continuing Medical Education (CME)?
Dates and Duration
Original Release Date: 08/10/2020
Expiration Date: 08/10/2023
Estimated Time to Complete: 11 hours
CME Credits Offered: 11.00
Accreditation
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The Stanford University School of Medicine designates this enduring material for a maximum of 11.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Disclosures
The Stanford University School of Medicine adheres to ACCME Criteria, Standards and Policies regarding industry support of continuing medical education. There are no relevant financial relationships with ACCME-defined commercial interests for anyone who was in control of the content of this activity.
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