This course introduces you to a framework for successful and ethical medical data mining. We will explore the variety of clinical data collected during the delivery of healthcare. You will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. We will also explore issues of fairness and bias that may arise when we leverage healthcare data to make decisions about patient care.
Introduction to Clinical Data
Introduction to Clinical Data
This course is part of AI in Healthcare Specialization
Instructors: Nigam Shah
24,704 already enrolled
Gain insight into a topic and learn the fundamentals.
4.7
(389 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 11 hours
Learn at your own pace
97%
Most learners liked this course
What you'll learn
How to apply a framework for medical data mining
Ethical use of data in healthcare decisions
How to make use of data that may be inaccurate in systematic ways
What makes a good research question and how to construct a data mining workflow answer it
Details to know
Shareable certificate
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Assessments
20 assignments
Taught in English
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This course is part of the AI in Healthcare Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 8 modules in this course
What's included
12 videos2 readings3 assignments
What's included
16 videos3 readings4 assignments1 plugin
What's included
12 videos2 readings3 assignments
What's included
18 videos2 readings3 assignments
What's included
19 videos4 readings3 assignments
What's included
11 videos3 readings3 assignments
What's included
7 videos2 readings
What's included
1 video3 readings1 assignment
Instructors
Instructor ratings
4.7 (118 ratings)Offered by
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Learner reviews
4.7
389 reviews
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Showing 3 of 389
MC
5
Reviewed on Dec 10, 2020
Great learning on uses of AI in healthcare and how to deal with ethical concerns
S
5
Reviewed on Apr 7, 2024
This course helps me a lot for how to frame clinical research question. How researchers make question
WB
5
Reviewed on Feb 20, 2023
The course is well organized and information dense - very efficient and very clearly explained. Highly recommend for a solid overview of clinical data in healthcare.
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Frequently asked questions
Dates and Duration
Original Release Date: 08/10/2023
Expiration Date: 08/10/2026
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.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.