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.
This course is part of the AI in Healthcare Specialization
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AI in Healthcare SpecializationStanford UniversityAbout this Course
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Course 2 of 5 in the
Beginner Level
Approx. 12 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
What you will 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
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 5 in the
Beginner Level
Approx. 12 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Offered by
Stanford University
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.
Syllabus - What you will learn from this course
1 hour to complete
Asking and answering questions via clinical data mining
1 hour to complete
12 videos (Total 19 min), 2 readings, 3 quizzes
2 hours to complete
Data available from Healthcare systems
2 hours to complete
16 videos (Total 32 min), 3 readings, 4 quizzes
1 hour to complete
Representing time, and timing of events, for clinical data mining
1 hour to complete
12 videos (Total 20 min), 2 readings, 3 quizzes
2 hours to complete
Creating analysis ready datasets from patient timelines
2 hours to complete
18 videos (Total 33 min), 2 readings, 3 quizzes
Reviews
- 5 stars69.23%
- 4 stars25.44%
- 3 stars4.14%
- 2 stars1.18%
TOP REVIEWS FROM INTRODUCTION TO CLINICAL DATA
by YXNov 4, 2020
Very clear and well-organized course. I have learned quite a bit about the different types of clinical data, why they are important, and how to transfer them to analytical useable data sets.
by TLDec 31, 2021
Very nice and accessible introduction to clinical data and the associated ethical considerations.
by SROct 26, 2020
Good introductory course covering key features of the various data that are gathered or used in health care. No prior knowledge about the topic is required.
by AMMay 27, 2022
Course was generally good -- final assessment questions were not always carefully worded nor proofread.
About the AI in Healthcare Specialization
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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