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Nigam Shah,
Steven Bagley,
and
David Magnus
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.
Read more
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.
Read more
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.
In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.
Register for this course and see more details by visiting:
OpenCourser.com/course/va423j/introduction
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What's inside
Syllabus
Asking and answering questions via clinical data mining
Data available from Healthcare systems
Representing time, and timing of events, for clinical data mining
Read more
Syllabus
Asking and answering questions via clinical data mining
Data available from Healthcare systems
Representing time, and timing of events, for clinical data mining
Read more
Creating analysis ready datasets from patient timelines
Handling unstructured healthcare data: text, images, signals
Putting the pieces together: Electronic phenotyping
Ethics
Course Conclusion
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Medical professionals will learn techniques for using healthcare data to answer clinical questions and make informed decisions
Explores issues of fairness and bias and how they may arise in making patient care decisions using healthcare data, a topic of growing importance
Taught by Nigam Shah and Steven Bagley both of whom are co-directors of Stanford's Clinical Artificial Intelligence Lab who also are recognized scientists at Google AI Healthcare
Taught by David Magnus, a pioneer in the field of bioethics, who directs Stanford's Center for Biomedical Ethics
Provides foundation for advanced topics in medical data mining
Requires students to complete prerequisites before enrolling, which may pose a barrier to entry
Save this course
Save Introduction to Clinical Data to your list so you can find it easily later:
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Reviews summary
Well-received clinical data overview
Learners say this course is a largely positive introduction to clinical data. Engaging assignments and practical examples help present key concepts, and the course effectively prepares students to understand the use of clinical data in healthcare.
Slides are helpful for clarity
"Perfect explanations and good quality materials. "
Instructor is engaging and well organized
"The course is well organized and information dense."
The instructor speaks too quickly to be easily understood
"The instructor could be confusing and a bit too brief sometimes..."
Videos are too short to provide enough detail
"Videos are too short, some are just seconds long."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Clinical Data with these
activities:
Refresh skills in data analysis and visualization
Show steps
Sharpen data analysis and visualization skills to effectively analyze and present healthcare data.
Browse courses on
Data Analysis
Show steps
-
Review online tutorials on data analysis and visualization.
-
Complete practice exercises using real-world healthcare data.
-
Attend a workshop or webinar on data analysis and visualization.
Refresh knowledge on healthcare systems
Show steps
Review the different types of healthcare systems and how they collect and use data to improve patient care.
Browse courses on
Healthcare Systems
Show steps
-
Review online resources about healthcare systems.
-
Read journal articles about the collection and use of medical data.
-
Attend a webinar on the latest trends in healthcare data analytics.
Review binary classifiers
Show steps
Refreshes knowledge of binary classifiers by reviewing the underlying concepts and their applications in real-world scenarios.
Browse courses on
Classification
Show steps
-
Study lecture notes or online resources on binary classifiers.
-
Solve practice problems involving binary classification tasks.
-
Review case studies of binary classifiers used in various domains.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Volunteer at a healthcare organization
Show steps
Gain practical experience in a healthcare setting and learn about the challenges and opportunities of using data to improve patient care.
Show steps
-
Identify a healthcare organization to volunteer at.
-
Contact the organization and inquire about volunteer opportunities.
-
Complete the necessary training and orientation.
-
Perform volunteer duties as assigned.
Create a comprehensive study guide
Show steps
Organizes and consolidates course materials, facilitating efficient review and knowledge retention.
Show steps
-
Gather all relevant course materials, including notes, assignments, and slides.
-
Review the materials and identify key concepts and topics.
-
Summarize and organize the information into a structured guide.
Follow tutorials on electronic phenotyping
Show steps
Gain a deeper understanding of the techniques used to identify and characterize patient populations based on their electronic health records.
Show steps
-
Identify online tutorials on electronic phenotyping.
-
Follow the tutorials and complete the practice exercises.
-
Apply the techniques to a real-world healthcare dataset.
Solve data mining algorithm exercises
Show steps
Reinforces understanding of data mining algorithms through regular practice, improving problem-solving skills and algorithm comprehension.
Browse courses on
Data Mining
Show steps
-
Identify online platforms or textbooks with data mining algorithm exercises.
-
Practice solving these exercises regularly.
-
Analyze the results and identify areas for improvement.
Practice creating analysis-ready datasets from patient timelines
Show steps
Develop the skills needed to prepare data for analysis by practicing with real-world patient data.
Browse courses on
Data Wrangling
Show steps
-
Download a dataset of patient timelines.
-
Clean and preprocess the data.
-
Create features and labels for analysis.
Explore time series analysis libraries
Show steps
Provides hands-on experience with time series analysis libraries, enhancing understanding of their functionalities and applications.
Browse courses on
Time Series Analysis
Show steps
-
Identify different time series analysis libraries in Python or R.
-
Follow guided tutorials to install and utilize these libraries for data preprocessing, feature engineering, and model building.
-
Experiment with different libraries to compare their capabilities and ease of use.
Create a dashboard to visualize healthcare data
Show steps
Develop the skills to present healthcare data in a clear and concise manner that supports decision-making.
Browse courses on
Data Visualization
Show steps
-
Identify the data to be visualized.
-
Select the appropriate visualization techniques.
-
Create the dashboard.
-
Test and refine the dashboard.
Attend industry conferences on data mining
Show steps
Provides opportunities to connect with professionals in the field, learn about industry best practices, and explore potential career paths.
Browse courses on
Data Mining
Show steps
-
Identify relevant data mining conferences.
-
Attend the conferences and participate in networking events.
-
Exchange ideas and knowledge with other attendees.
Contribute to open-source data mining projects
Show steps
Engages students in the open-source community, enhancing their understanding of data mining tools and fostering collaboration with fellow developers.
Browse courses on
Data Mining
Show steps
-
Identify open-source data mining projects on platforms like GitHub.
-
Read the project documentation and identify ways to contribute.
-
Make code contributions, report bugs, or provide documentation improvements.
Create a presentation on the ethical issues of using healthcare data
Show steps
Develop a deeper understanding of the ethical implications of using healthcare data and how to address them.
Browse courses on
Data Privacy
Show steps
-
Research the ethical issues surrounding the use of healthcare data.
-
Develop a presentation outline.
-
Create a visually appealing presentation.
-
Practice delivering the presentation.
Develop a data visualization dashboard
Show steps
Applies knowledge of data visualization techniques to create an interactive dashboard, fostering a deeper understanding of data storytelling and communication.
Browse courses on
Data Visualization
Show steps
-
Gather and clean the necessary data.
-
Choose appropriate visualization techniques and tools.
-
Design and develop the interactive dashboard.
-
Present the dashboard and explain the insights derived from the data.
Participate in a data mining hackathon
Show steps
Provides a hands-on experience in applying data mining techniques to real-world problems, fostering collaboration and problem-solving skills.
Browse courses on
Data Mining
Show steps
-
Identify and register for a data mining hackathon.
-
Form a team with complementary skills.
-
Collaborate to develop and implement a data mining solution.
Refresh skills in data analysis and visualization
Show steps
Sharpen data analysis and visualization skills to effectively analyze and present healthcare data.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Review online tutorials on data analysis and visualization.
- Complete practice exercises using real-world healthcare data.
- Attend a workshop or webinar on data analysis and visualization.
Refresh knowledge on healthcare systems
Show steps
Review the different types of healthcare systems and how they collect and use data to improve patient care.
Browse courses on
Healthcare Systems
Show steps
Show steps
Show steps
- Review online resources about healthcare systems.
- Read journal articles about the collection and use of medical data.
- Attend a webinar on the latest trends in healthcare data analytics.
Review binary classifiers
Show steps
Refreshes knowledge of binary classifiers by reviewing the underlying concepts and their applications in real-world scenarios.
Browse courses on
Classification
Show steps
Show steps
Show steps
- Study lecture notes or online resources on binary classifiers.
- Solve practice problems involving binary classification tasks.
- Review case studies of binary classifiers used in various domains.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Volunteer at a healthcare organization
Show steps
Gain practical experience in a healthcare setting and learn about the challenges and opportunities of using data to improve patient care.
Show steps
Show steps
Show steps
- Identify a healthcare organization to volunteer at.
- Contact the organization and inquire about volunteer opportunities.
- Complete the necessary training and orientation.
- Perform volunteer duties as assigned.
Create a comprehensive study guide
Show steps
Organizes and consolidates course materials, facilitating efficient review and knowledge retention.
Show steps
Show steps
Show steps
- Gather all relevant course materials, including notes, assignments, and slides.
- Review the materials and identify key concepts and topics.
- Summarize and organize the information into a structured guide.
Follow tutorials on electronic phenotyping
Show steps
Gain a deeper understanding of the techniques used to identify and characterize patient populations based on their electronic health records.
Show steps
Show steps
Show steps
- Identify online tutorials on electronic phenotyping.
- Follow the tutorials and complete the practice exercises.
- Apply the techniques to a real-world healthcare dataset.
Solve data mining algorithm exercises
Show steps
Reinforces understanding of data mining algorithms through regular practice, improving problem-solving skills and algorithm comprehension.
Browse courses on
Data Mining
Show steps
Show steps
Show steps
- Identify online platforms or textbooks with data mining algorithm exercises.
- Practice solving these exercises regularly.
- Analyze the results and identify areas for improvement.
Practice creating analysis-ready datasets from patient timelines
Show steps
Develop the skills needed to prepare data for analysis by practicing with real-world patient data.
Browse courses on
Data Wrangling
Show steps
Show steps
Show steps
- Download a dataset of patient timelines.
- Clean and preprocess the data.
- Create features and labels for analysis.
Explore time series analysis libraries
Show steps
Provides hands-on experience with time series analysis libraries, enhancing understanding of their functionalities and applications.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Identify different time series analysis libraries in Python or R.
- Follow guided tutorials to install and utilize these libraries for data preprocessing, feature engineering, and model building.
- Experiment with different libraries to compare their capabilities and ease of use.
Create a dashboard to visualize healthcare data
Show steps
Develop the skills to present healthcare data in a clear and concise manner that supports decision-making.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify the data to be visualized.
- Select the appropriate visualization techniques.
- Create the dashboard.
- Test and refine the dashboard.
Attend industry conferences on data mining
Show steps
Provides opportunities to connect with professionals in the field, learn about industry best practices, and explore potential career paths.
Browse courses on
Data Mining
Show steps
Show steps
Show steps
- Identify relevant data mining conferences.
- Attend the conferences and participate in networking events.
- Exchange ideas and knowledge with other attendees.
Contribute to open-source data mining projects
Show steps
Engages students in the open-source community, enhancing their understanding of data mining tools and fostering collaboration with fellow developers.
Browse courses on
Data Mining
Show steps
Show steps
Show steps
- Identify open-source data mining projects on platforms like GitHub.
- Read the project documentation and identify ways to contribute.
- Make code contributions, report bugs, or provide documentation improvements.
Create a presentation on the ethical issues of using healthcare data
Show steps
Develop a deeper understanding of the ethical implications of using healthcare data and how to address them.
Browse courses on
Data Privacy
Show steps
Show steps
Show steps
- Research the ethical issues surrounding the use of healthcare data.
- Develop a presentation outline.
- Create a visually appealing presentation.
- Practice delivering the presentation.
Develop a data visualization dashboard
Show steps
Applies knowledge of data visualization techniques to create an interactive dashboard, fostering a deeper understanding of data storytelling and communication.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather and clean the necessary data.
- Choose appropriate visualization techniques and tools.
- Design and develop the interactive dashboard.
- Present the dashboard and explain the insights derived from the data.
Participate in a data mining hackathon
Show steps
Provides a hands-on experience in applying data mining techniques to real-world problems, fostering collaboration and problem-solving skills.
Browse courses on
Data Mining
Show steps
Show steps
Show steps
- Identify and register for a data mining hackathon.
- Form a team with complementary skills.
- Collaborate to develop and implement a data mining solution.
Career center
Learners who complete Introduction to Clinical Data will develop knowledge and skills
that may be useful to these careers:
Software Engineer
Software Engineer
The course provides a strong foundation for Software Engineers seeking to work with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Epidemiologist
Epidemiologist
The course provides a strong foundation for Epidemiologists seeking to work with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Health Informatics Specialist
Health Informatics Specialist
The course provides a strong foundation for Health Informatics Specialists seeking to work with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Data Scientist
Data Scientist
Data Scientists may find this course hữu ích as it provides a strong foundation for working with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Pharmaceutical Sales Representative
Pharmaceutical Sales Representative
The course provides a strong foundation for Pharmaceutical Sales Representatives seeking to work with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Healthcare Consultant
Healthcare Consultant
Healthcare Consultants may find this course hữu ích as it provides a strong foundation for working with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Health Policy Analyst
Health Policy Analyst
Health Policy Analysts may find this course hữu ích as it provides a strong foundation for working with clinical healthcare data. The course teaches learners how to ask and answer questions via medical data mining. It also teaches the basics for representing time, and timing of events, for clinical data mining. With this knowledge, learners can apply computational procedures to important clinical questions and make a meaningful impact to the field of healthcare through data.
Clinical Data Manager
Clinical Data Manager
This course may be useful for Clinical Data Managers looking to expand their knowledge of clinical data mining and its applications in healthcare. The course includes modules on creating analysis ready datasets from patient timelines, handling unstructured healthcare data, and the ethical considerations of leveraging healthcare data.
Public Health Researcher
Public Health Researcher
This course may be useful for Public Health Researchers looking to expand their knowledge of clinical data mining and its applications in healthcare. The course includes modules on creating analysis ready datasets from patient timelines, handling unstructured healthcare data, and the ethical considerations of leveraging healthcare data.
Medical Device Sales Representative
Medical Device Sales Representative
This course may be useful for Medical Device Sales Representatives looking to expand their knowledge of clinical data mining and its applications in healthcare. The course includes modules on creating analysis ready datasets from patient timelines, handling unstructured healthcare data, and the ethical considerations of leveraging healthcare data.
Clinical Research Associate
Clinical Research Associate
This course may be useful for Clinical Research Associates looking to enhance their knowledge of clinical data mining and data analysis. The course introduces learners to constructing analysis-ready datasets. It also includes a module on handling unstructured healthcare data and putting the pieces together for electronic phenotyping.
Healthcare Analyst
Healthcare Analyst
This course may be useful for Healthcare Analysts looking to broaden their knowledge of clinical data mining and its applications to patient care. The course includes modules on creating analysis ready datasets from patient timelines, handling unstructured healthcare data, and the ethical pitfalls of leveraging healthcare data.
Biostatistician
Biostatistician
This course may be useful for Biostatisticians looking to broaden their knowledge of clinical data mining and its applications to patient care. The course includes modules on creating analysis ready datasets from patient timelines, handling unstructured healthcare data, and the ethical pitfalls of leveraging healthcare data.
Healthcare Administrator
Healthcare Administrator
This course may be useful for Healthcare Administrators looking to broaden their knowledge of clinical data mining and its applications to patient care. The course includes modules on creating analysis ready datasets from patient timelines, handling unstructured healthcare data, and the ethical pitfalls of leveraging healthcare data.
Medical Writer
Medical Writer
This course may be useful for Medical Writers looking to enhance their understanding of clinical data mining and its applications to patient care. The course includes a module on the ethical pitfalls of leveraging healthcare data, which is an important consideration for Medical Writers communicating about clinical research and data.
For more career information including salaries, visit:
OpenCourser.com/course/va423j/introduction
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Clinical Data.
Is written by Google Health experts specializing in clinical data science. It is an essential reference for anyone interested in clinical data science at scale.
Save
Although this book is more technically challenging, it covers healthcare topics that are not present in the course material.
Save
Discusses the use of artificial intelligence in medicine. It covers topics such as machine learning, natural language processing, and the potential of AI to transform healthcare.
This textbook provides a comprehensive overview of statistical methods used in medical research, including descriptive statistics, inferential statistics, and regression analysis.
Provides a comprehensive overview of nursing informatics. It valuable resource for anyone who wants to learn more about this topic.
Offers a comprehensive overview of data analytics in healthcare, including the challenges and opportunities of using data to improve patient care.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/va423j/introduction
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Level
Introductory
Via
Coursera
Institution
Stanford University
Instructors
Nigam Shah
Steven Bagley
David Magnus
Language
English
Transcripts
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Français
Português
Deutsch
Italiano
中文
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This course belongs to a
collection
called
AI in Healthcare. It's comprised of five courses:
- AI in Healthcare Capstone
- Introduction to Healthcare
- Evaluations of AI Applications in Healthcare
- Fundamentals of Machine Learning for Healthcare
- Introduction to Clinical Data (viewing)
Good to know
Medical professionals will learn techniques for using healthcare data to answer clinical questions and make informed decisions
Explores issues of fairness and bias and how they may arise in making patient care decisions using healthcare data, a topic of growing importance
Taught by Nigam Shah and Steven Bagley both of whom are co-directors of Stanford's Clinical Artificial Intelligence Lab who also are recognized scientists at Google AI Healthcare
Taught by David Magnus, a pioneer in the field of bioethics, who directs Stanford's Center for Biomedical Ethics
Provides foundation for advanced topics in medical data mining
Requires students to complete prerequisites before enrolling, which may pose a barrier to entry
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