We may earn an affiliate commission when you visit our partners.
Laura K. Wiley, PhD
This course teaches you the fundamentals of computational phenotyping, a biomedical informatics method for identifying patient populations. In this course you will learn how different clinical data types perform when trying to identify patients with a particular disease or trait. You will also learn how to program different data manipulations and combinations to increase the complexity and improve the performance of your algorithms. Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop a computational phenotyping algorithm to identify patients who have hypertension. You will complete this work using a real clinical data set while using a free, online computational environment for data science hosted by our Industry Partner Google Cloud.
Register for this course and see more details by visiting:
OpenCourser.com/course/1j3s1y/identifying
Three deals to help you save
We found three deals and offers that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until December 12
Annual Subscription Savings
Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.
Only $239!
Valid for a limited time only
Future-proof your career
Access O'Reilly books, live events, courses, and more. Save with an annual subscription.
Take
15%
off
What's inside
Syllabus
Introduction: Identifying Patient Populations
Learn about computational phenotyping and how to use the technique to identify patient populations.
Read more
Syllabus
Introduction: Identifying Patient Populations
Learn about computational phenotyping and how to use the technique to identify patient populations.
Read more
Tools: Clinical Data Types
Understand how different clinical data types can be used to identify patient populations. Begin developing a computational phenotyping algorithm to identify patients with type II diabetes.
Techniques: Data Manipulations and Combinations
Learn how to manipulate individual data types and combine multiple data types in computational phenotyping algorithms. Develop a more sophisticated computational phenotyping algorithm to identify patients with type II diabetes.
Techniques: Algorithm Selection and Portability
Understand how to select a single "best" computational phenotyping algorithm. Finalize and justify a phenotyping algorithm for type II diabetes.
Practical Application: Develop a Computational Phenotyping Algorithm to Identify Patients with Hypertension
Put your new skills to the test - develop an computational phenotyping algorithm to identify patients with hypertension.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Tailored to learners interested in biomedical informatics, focusing on identifying patient populations through computation
Beginner-friendly, providing a solid foundation in computational phenotyping
Covers advanced topics like data manipulation and algorithm selection, enhancing learners' skills in developing sophisticated phenotyping algorithms
Practical, hands-on experience via a real-world project, where learners develop an algorithm to identify patients with hypertension
Leverages Google Cloud's free computational environment, providing learners with access to industry-standard tools
Save this course
Save Identifying Patient Populations to your list so you can find it easily later:
Save
Save
Reviews summary
Introductory patient population identification course
According to students, this introductory course on identifying patient populations requires a working knowledge of R, which is not provided within the course. Hands-on teaching is used in addition to lectures throughout the course, but learners found this course to have many difficult exams.
Incorporates hands-on teaching methods.
"The instructor does a great job of providing hands-on teaching in addition to lecture."
Learners need to know R before taking this course.
"However, this course required a lot of knowledge of R, which wasn't provided in the introductory course."
Exams in this course are difficult.
"However, this course required a lot of knowledge of R, which wasn't provided in the introductory course."
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 Identifying Patient Populations with these
activities:
Review high school math principles
Show steps
To ensure success in this course, it would be beneficial to ensure knowledge and understanding of high school level mathematics.
Browse courses on
Trigonometry
Show steps
-
Review the functions and rules of algebra
-
Practice solving equations and inequalities
-
Review trigonometry basics, including the trigonometric ratios, identities, and graphs of trigonometric functions
Join a study group or discussion forum on computational phenotyping
Show steps
Participating in a study group or discussion forum will allow you to connect with other students, share ideas, and get feedback on your work.
Show steps
-
Find a study group or discussion forum online or in your local area
-
Attend the meetings or participate in the discussions
-
Share your work and get feedback from others
Follow guided tutorials on computational phenotyping
Show steps
Guided tutorials will provide you with structured and step-by-step instructions on how to perform computational phenotyping tasks.
Show steps
-
Find guided tutorials online or in textbooks
-
Follow the instructions in the tutorial
-
Complete the exercises and activities provided in the tutorial
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve practice problems on computational phenotyping
Show steps
Solving practice problems will help you develop your skills in computational phenotyping and improve your understanding of the concepts.
Show steps
-
Find practice problems online or in textbooks
-
Work through the problems step-by-step
-
Check your answers against the provided solutions
Develop a computational phenotyping algorithm
Show steps
Developing a computational phenotyping algorithm will allow you to apply the concepts you have learned in the course and create something tangible that can be used to identify patient populations.
Show steps
-
Choose a specific disease or condition to focus on
-
Gather and prepare the necessary data
-
Develop and implement the algorithm
-
Evaluate the performance of the algorithm
Contribute to open-source projects related to computational phenotyping
Show steps
Contributing to open-source projects will allow you to learn from others, stay up-to-date on the latest developments in the field, and make a valuable contribution to the community.
Show steps
-
Find open-source projects related to computational phenotyping
-
Review the project documentation
-
Identify ways to contribute to the project
-
Submit your contributions to the project
Start a project to apply computational phenotyping to a real-world problem
Show steps
Starting a project will allow you to apply the concepts you have learned in the course to a real-world problem and make a meaningful contribution to the field.
Show steps
-
Identify a real-world problem that can be addressed using computational phenotyping
-
Gather and prepare the necessary data
-
Develop and implement a computational phenotyping algorithm
-
Evaluate the performance of the algorithm
-
Write a report or presentation on your findings
Review high school math principles
Show steps
To ensure success in this course, it would be beneficial to ensure knowledge and understanding of high school level mathematics.
Browse courses on
Trigonometry
Show steps
Show steps
Show steps
- Review the functions and rules of algebra
- Practice solving equations and inequalities
- Review trigonometry basics, including the trigonometric ratios, identities, and graphs of trigonometric functions
Join a study group or discussion forum on computational phenotyping
Show steps
Participating in a study group or discussion forum will allow you to connect with other students, share ideas, and get feedback on your work.
Show steps
Show steps
Show steps
- Find a study group or discussion forum online or in your local area
- Attend the meetings or participate in the discussions
- Share your work and get feedback from others
Follow guided tutorials on computational phenotyping
Show steps
Guided tutorials will provide you with structured and step-by-step instructions on how to perform computational phenotyping tasks.
Show steps
Show steps
Show steps
- Find guided tutorials online or in textbooks
- Follow the instructions in the tutorial
- Complete the exercises and activities provided in the tutorial
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve practice problems on computational phenotyping
Show steps
Solving practice problems will help you develop your skills in computational phenotyping and improve your understanding of the concepts.
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks
- Work through the problems step-by-step
- Check your answers against the provided solutions
Develop a computational phenotyping algorithm
Show steps
Developing a computational phenotyping algorithm will allow you to apply the concepts you have learned in the course and create something tangible that can be used to identify patient populations.
Show steps
Show steps
Show steps
- Choose a specific disease or condition to focus on
- Gather and prepare the necessary data
- Develop and implement the algorithm
- Evaluate the performance of the algorithm
Contribute to open-source projects related to computational phenotyping
Show steps
Contributing to open-source projects will allow you to learn from others, stay up-to-date on the latest developments in the field, and make a valuable contribution to the community.
Show steps
Show steps
Show steps
- Find open-source projects related to computational phenotyping
- Review the project documentation
- Identify ways to contribute to the project
- Submit your contributions to the project
Start a project to apply computational phenotyping to a real-world problem
Show steps
Starting a project will allow you to apply the concepts you have learned in the course to a real-world problem and make a meaningful contribution to the field.
Show steps
Show steps
Show steps
- Identify a real-world problem that can be addressed using computational phenotyping
- Gather and prepare the necessary data
- Develop and implement a computational phenotyping algorithm
- Evaluate the performance of the algorithm
- Write a report or presentation on your findings
Career center
Learners who complete Identifying Patient Populations will develop knowledge and skills
that may be useful to these careers:
Biostatistician
Biostatistician
Biostatisticians use statistics to design and interpret studies for clinical trials and solve biomedical research problems. Depending on their specialization, a Biostatistician may work on laboratory research or in a more applied setting, helping to develop new drugs, treatments, and devices. This course may help build a foundation for a Biostatistician by teaching learners how to identify patient populations using computational phenotyping algorithms.
Data Scientist
Data Scientist
Data Scientists use their knowledge of math, statistics, and computer science to extract meaningful insights from raw data. They develop new algorithms and tools for data analysis and help organizations make data-driven decisions. This course may help build a foundation for a Data Scientist by teaching them how to identify patient populations using computational phenotyping algorithms.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes of disease and develop strategies to prevent and control their spread. They study the distribution and patterns of health events and diseases in populations. This course may help build a foundation for an Epidemiologist by teaching them how to identify patient populations using computational phenotyping algorithms.
Health Informatics Specialist
Health Informatics Specialist
Health Informatics Specialists use their knowledge of healthcare and information technology to improve the quality and efficiency of healthcare delivery. They develop and implement new health information systems and help organizations make data-driven decisions. This course may help build a foundation for a Health Informatics Specialist by teaching learners how to identify patient populations using computational phenotyping algorithms.
Medical Informatics Engineer
Medical Informatics Engineer
Medical Informatics Engineers use their knowledge of engineering and medicine to develop new technologies for healthcare. They design and implement new medical devices, software, and systems. This course may help build a foundation for a Medical Informatics Engineer by teaching them how to identify patient populations using computational phenotyping algorithms.
Pharmacist
Pharmacist
Pharmacists dispense medications and provide counseling to patients on how to use them safely and effectively. They also work with doctors and other healthcare professionals to manage patient care. This course may help build a foundation for a Pharmacist by teaching learners how to identify patient populations using computational phenotyping algorithms.
Public Health Analyst
Public Health Analyst
Public Health Analysts use their knowledge of public health to develop and implement programs to improve the health of communities. They work with government agencies, non-profit organizations, and other stakeholders to address public health issues. This course may help build a foundation for a Public Health Analyst by teaching learners how to identify patient populations using computational phenotyping algorithms.
Research Scientist
Research Scientist
Research Scientists conduct original research in a variety of fields, including biomedical sciences, engineering, and computer science. They design and conduct experiments, analyze data, and publish their findings in peer-reviewed journals. This course may help build a foundation for a Research Scientist by teaching learners how to identify patient populations using computational phenotyping algorithms.
Statistician
Statistician
Statisticians use statistics to collect, analyze, interpret, and present data. They work in a variety of fields, including healthcare, finance, and marketing. This course may help build a foundation for a Statistician by teaching learners how to identify patient populations using computational phenotyping algorithms.
Biomedical Engineer
Biomedical Engineer
Biomedical Engineers use their knowledge of engineering and medicine to develop new technologies for healthcare. They design and implement new medical devices, software, and systems. This course may be useful for a Biomedical Engineer who is interested in developing new computational tools for identifying patient populations.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and data analysis to help organizations make better decisions. They work with stakeholders to identify and solve business problems. This course may be useful for a Business Analyst who is interested in using computational phenotyping algorithms to identify patient populations for market research or other purposes.
Clinical Research Coordinator
Clinical Research Coordinator
Clinical Research Coordinators manage clinical trials and other research studies. They work with researchers, patients, and other healthcare professionals to ensure that studies are conducted according to protocol. This course may be useful for a Clinical Research Coordinator who is interested in using computational phenotyping algorithms to identify patient populations for clinical trials.
Healthcare Consultant
Healthcare Consultant
Healthcare Consultants provide advice to healthcare organizations on how to improve their operations and efficiency. They work with clients to identify and solve problems, and develop and implement new solutions. This course may be useful for a Healthcare Consultant who is interested in using computational phenotyping algorithms to identify patient populations for new programs or services.
Medical Writer
Medical Writer
Medical Writers create and edit written content for a variety of audiences, including patients, healthcare professionals, and the general public. They work with medical experts to ensure that the content is accurate and up-to-date. This course may be useful for a Medical Writer who is interested in writing about computational phenotyping algorithms and their applications in healthcare.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts ensure that products and services meet quality standards. They work with teams to identify and resolve problems, and develop and implement new quality control measures. This course may be useful for a Quality Assurance Analyst who is interested in using computational phenotyping algorithms to identify patient populations for quality improvement initiatives.
For more career information including salaries, visit:
OpenCourser.com/course/1j3s1y/identifying
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
Identifying Patient Populations.
Provides a comprehensive overview of machine learning in medicine, including its history, methods, and applications. It valuable resource for both researchers and clinicians who want to learn more about this rapidly growing field.
Provides a comprehensive overview of deep learning for healthcare, including its history, methods, and applications. It valuable resource for both researchers and clinicians who want to learn more about this rapidly growing field.
Provides a comprehensive overview of health informatics, including its history, methods, and applications. It valuable resource for both researchers and clinicians who want to learn more about this important topic.
Provides a comprehensive overview of statistical methods in medical research, including their application in clinical trials, observational studies, and meta-analyses. It is an excellent resource for both researchers and clinicians who want to learn more about this important topic.
Save
Provides a comprehensive overview of epidemiology, including its history, methods, and applications. It is an excellent resource for both researchers and clinicians who want to learn more about this important topic.
Provides a basic overview of medical statistics, including its history, methods, and applications. It good resource for beginners who want to learn more about this topic.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1j3s1y/identifying
Share
Similar courses
Here are nine courses similar to
Identifying Patient Populations.
Clinical Natural Language Processing
OpenCourser.com/course/ewh57i/clinical
Clinical Natural Language Processing
Most relevant
Introduction to Clinical Data Science
OpenCourser.com/course/0u98hb/introduction
Introduction to Clinical Data Science
Most relevant
Value-Based Care: Managing Processes to Improve Outcomes
OpenCourser.com/course/5fsybr/value
Value-Based Care: Managing Processes to Improve Outcomes
Most relevant
Foundations of Originator and Biosimilar Biologics: for Patients and Caregivers
OpenCourser.com/course/u2kbkv/foundations
Foundations of Originator and Biosimilar Biologics: for...
Medicines Adherence: Supporting Patients with Their Treatment
OpenCourser.com/course/1o5u5x/futurelearn
Medicines Adherence: Supporting Patients with Their...
Drug Development
OpenCourser.com/course/yciese/drug
Drug Development
Computational Thinking with JavaScript 2: Model & Analyse
OpenCourser.com/course/ywkrt0/computational
Computational Thinking with JavaScript 2: Model & Analyse
CERTaIN: Observational Studies and Registries
OpenCourser.com/course/zdxofl/certain
CERTaIN: Observational Studies and Registries
XR in Healthcare Education and Clinical Practice
OpenCourser.com/course/o9zaz3/xr
XR in Healthcare Education and Clinical Practice
Effort
5 weeks of study, 2-4 hours/week
Level
Intermediate
Via
Coursera
Institution
University of Colorado System
Instructor
Laura K. Wiley, PhD
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
Bahasa Indonesia
ไทย
қазақша
This course belongs to a
collection
called
Clinical Data Science. It's comprised of six courses:
Good to know
Tailored to learners interested in biomedical informatics, focusing on identifying patient populations through computation
Beginner-friendly, providing a solid foundation in computational phenotyping
Covers advanced topics like data manipulation and algorithm selection, enhancing learners' skills in developing sophisticated phenotyping algorithms
Practical, hands-on experience via a real-world project, where learners develop an algorithm to identify patients with hypertension
Leverages Google Cloud's free computational environment, providing learners with access to industry-standard tools
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser