Health Data Science Foundation
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Health Data Science Foundation
This course is part of Deep Learning for Healthcare Specialization
Instructor: Jimeng Sun
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What you'll learn
Machine Learning, Health Data Processing
Skills you'll gain
- Artificial Intelligence and Machine Learning (AI/ML)
- Applied Machine Learning
- Medical Science and Research
- Model Evaluation
- Machine Learning Methods
- Health Care
- Deep Learning
- Machine Learning Algorithms
- Machine Learning
- Supervised Learning
- Program Development
- Artificial Neural Networks
- Health Informatics
- Unsupervised Learning
Tools you'll learn
Details to know
4 assignments
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There are 4 modules in this course
This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.
We cover deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project. The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.
In the introduction we will introduce the topic of the course and present the background information.
What's included
3 videos3 readings1 assignment1 programming assignment1 discussion prompt
3 videosβ’Total 26 minutes
- Welcome to this course!β’3 minutes
- Introduction: Part 1β’11 minutes
- Introduction: Part 2β’12 minutes
3 readingsβ’Total 100 minutes
- About this courseβ’10 minutes
- Slides: Introductionβ’30 minutes
- Textbook Chapter 1 (Introduction)β’60 minutes
1 assignmentβ’Total 30 minutes
- Introductionβ’30 minutes
1 programming assignmentβ’Total 180 minutes
- Lab 1β’180 minutes
1 discussion promptβ’Total 10 minutes
- Welcome Forumβ’10 minutes
Health Data are generated in many different categories of medical services. We'll take a closer look at these, and what this means for Health Data standards.
What's included
8 videos3 readings1 assignment1 programming assignment
8 videosβ’Total 73 minutes
- Health Data - Introductionβ’6 minutes
- Health Data: EHR, Notesβ’13 minutes
- Health Data: Claims, Signalsβ’9 minutes
- Health Data: Images, Literature, Drugsβ’11 minutes
- Health Data Standards: Intro & ICDβ’11 minutes
- Health Data Standards: CPT, LOINC, NDCβ’7 minutes
- Health Data Standards: SNOMEDβ’9 minutes
- Health Data Standards: UMLSβ’7 minutes
3 readingsβ’Total 100 minutes
- Slides: Health Dataβ’30 minutes
- Slides: Health Data Standardsβ’10 minutes
- Textbook Chapter 2 (Health Data)β’60 minutes
1 assignmentβ’Total 30 minutes
- Health Data β’30 minutes
1 programming assignmentβ’Total 180 minutes
- Homework 1β’180 minutes
The topic of this week is Machine Learning. We'll look at
What's included
9 videos4 readings1 assignment1 programming assignment
9 videosβ’Total 89 minutes
- Prediction Targetβ’6 minutes
- Cohort Constructionβ’11 minutes
- Feature Constructionβ’10 minutes
- Predictive Model and Evaluationβ’7 minutes
- Dimensionality Reductionβ’10 minutes
- Clusteringβ’5 minutes
- Performance Metricsβ’19 minutes
- Classification Metricsβ’7 minutes
- Regression and Clustering Metricsβ’14 minutes
4 readingsβ’Total 90 minutes
- Slides: Supervised Learningβ’10 minutes
- Slides: Unsupervised Learningβ’10 minutes
- Slides: Evaluationβ’10 minutes
- Textbook Chapter 3 (Machine Learning Basics)β’60 minutes
1 assignmentβ’Total 30 minutes
- Machine Learning Basicsβ’30 minutes
1 programming assignmentβ’Total 180 minutes
- Lab 2β’180 minutes
What's included
4 videos2 readings1 assignment1 programming assignment1 plugin
4 videosβ’Total 37 minutes
- Single Neuron Basicsβ’7 minutes
- Training a Single Neuron: SGDβ’11 minutes
- Forward and Backward Computationβ’5 minutes
- Multilayer Neural Networkβ’14 minutes
2 readingsβ’Total 70 minutes
- Slides: Deep Neural Networksβ’10 minutes
- Textbook Chapter 4 (Deep Neural Networks (DNN))β’60 minutes
1 assignmentβ’Total 30 minutes
- Deep Neural Networksβ’30 minutes
1 programming assignmentβ’Total 180 minutes
- Homework 2 (Neural Network)β’180 minutes
1 pluginβ’Total 15 minutes
- How was the course?β’15 minutes
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