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URL: https://www.coursera.org/learn/machine-learning-for-healthcare-professionals

⇱ Machine Learning for Healthcare Professionals | Coursera

Machine Learning for Healthcare Professionals

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Machine Learning for Healthcare Professionals

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Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

There are 4 modules in this course

Examines data mining perspectives and methods in a healthcare context. Introduces the theoretical foundations for major data mining methods and studies how to select and use the appropriate data mining method and the major advantages for each. Students are exposed to contemporary data mining software applications and basic programming skills. Focuses on solving real-world problems, which require data cleaning, data transformation, and data modeling.

In this module, you'll learn about some independent organizations involved in evaluating algorithms, SPIRIT-AI and CONSORT-AI. These are members of the Coalition for Health IT (CHAI). You'll also refresh yourself on the development steps of an AI Algorithm, focusing primarily on where your dataset comes from.

What's included

6 videos8 readings3 assignments2 discussion prompts

6 videos•Total 19 minutes
  • Meet Your Faculty: Paul Cerrato•1 minute
  • Meet Your Faculty: Sonya Makhni•2 minutes
  • Addressing Inequities in Datasets and Algorithms•4 minutes
  • The Coalition for Health IT•3 minutes
  • Dataset Construction•5 minutes
  • Dataset Preparation•4 minutes
8 readings•Total 180 minutes
  • Welcome to Machine Learning for Healthcare Professionals•1 minute
  • Syllabus•10 minutes
  • Recommended Prior Knowledge: Basic Statistics•5 minutes
  • Recommended Prior Knowledge: How to Read Journal Articles•30 minutes
  • Module Overview•1 minute
  • Lesson Resources•66 minutes
  • Lesson Resources•66 minutes
  • Module 1 Summary•1 minute
3 assignments•Total 15 minutes
  • Module Quiz•9 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
2 discussion prompts•Total 100 minutes
  • Welcome to the Course!•10 minutes
  • Inequities in Healthcare•90 minutes

This Module will concentrate on the value of Machine learning in analyzing patient data, including data generated by large clinical trials. You’ll learn about the benefits of subgroup analysis and take a closer look at a large randomized trial conducted by Mayo Clinic investigators. We’ll also explore the difference between correlation and causality, including some unexpected insights about their relationship.

What's included

6 videos3 readings3 assignments1 discussion prompt

6 videos•Total 17 minutes
  • Module Overview•1 minute
  • Analyzing the EAGLE Study•3 minutes
  • Benefits and Risks of Large Language Models Part 1•4 minutes
  • Benefits and Risks of Large Language Models Part 2•3 minutes
  • Internal/External Validation•4 minutes
  • Clinical Validation Studies•2 minutes
3 readings•Total 13 minutes
  • Subgroup Analysis in Diabetes•5 minutes
  • Correlation vs. Causality•7 minutes
  • Module Summary•1 minute
3 assignments•Total 16 minutes
  • Module Quiz•10 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
1 discussion prompt•Total 90 minutes
  • Benefits and Risks of Large Language Models•90 minutes

In this module we’ll examine the challenge of delivering AI based algorithms in the real world. What works in an AI Lab doesn't always translate at the bedside. With that in mind, we'll discuss the need for creating a delivery system that will help you incorporate these tools into everyday workflows.

What's included

4 videos2 readings5 assignments1 discussion prompt

4 videos•Total 8 minutes
  • Module Overview•0 minutes
  • Developing Delivery Method for Healthcare AI•3 minutes
  • Reducing Cognitive Load in Machine Learning•3 minutes
  • Delivering AI/Limitations•2 minutes
2 readings•Total 11 minutes
  • Governmental Regulations Impact AI Algorithms•10 minutes
  • Module Summary•1 minute
5 assignments•Total 22 minutes
  • Module Quiz•10 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
1 discussion prompt•Total 90 minutes
  • AI in Workflows•90 minutes

In this module, you’ll gaze into our crystal ball to figure out which AI tools are likely to endure. You’ll take a closer look at conversational tech, generative AI and several Mayo Clinic digital solutions that will transform healthcare in the next few years.

What's included

8 videos3 readings6 assignments1 discussion prompt

8 videos•Total 22 minutes
  • Module Overview•1 minute
  • Conversational Tech Tools•3 minutes
  • High Tech vs. High Touch Patient Care•3 minutes
  • Mayo Clinic Digital Solutions•3 minutes
  • The Future/Why Has the Future Not Arrived?•4 minutes
  • The Future of Digital Health•2 minutes
  • Developing a Successful Intervention•3 minutes
  • Post-Launch Monitoring•3 minutes
3 readings•Total 11 minutes
  • Generative AI and Interactive Bots•7 minutes
  • Module Summary•1 minute
  • Course Summary•3 minutes
6 assignments•Total 25 minutes
  • Module Quiz•10 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
  • Check Your Knowledge•3 minutes
1 discussion prompt•Total 90 minutes
  • How We Can Control AI•90 minutes

Instructor

Northeastern University
2 Courses•2,252 learners

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