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
25,505 already enrolled
Gain insight into a topic and learn the fundamentals.
4.7
(397 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
Skills you'll gain
- Data Analysis
- Medical Records
- Clinical Data Management
- Unstructured Data
- Data Ethics
- Healthcare Industry Knowledge
- Medical Science and Research
- Health Systems
- Data Quality
- Data Mining
- Electronic Medical Record
- Timelines
- Applied Machine Learning
- Analytics
- Data Wrangling
- Text Mining
- Health Information Management and Medical Records
- Clinical Trials
- Clinical Research
- Feature Engineering
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
20 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the AI in Healthcare Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
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 (119 ratings)Offered by
Recommended if you're interested in Data Analysis
University of Colorado System
Imperial College London
Johns Hopkins University
Johns Hopkins University
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
4.7
397 reviews
- 5 stars
74.37%
- 4 stars
19.34%
- 3 stars
4.52%
- 2 stars
1%
- 1 star
0.75%
Showing 3 of 397
LO
4
Reviewed on May 31, 2022
Good introductory course, although I must admit I was expecting a little bit a more hands-on approach. Some instructors speak very fast, so I had to keep replaying the video.
FW
5
Reviewed on Dec 28, 2022
Excellent intro with the right amount of information to provide a good overview of the subject without confusing
CC
5
Reviewed on Jul 1, 2021
I like this course because duration that instrutors teach it isn't too lone it easy to understand. And you can gain more your skills.
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
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.