Fundamentals of Machine Learning for Healthcare from Coursera

Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles.

This course will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare.

The course will empower those with non-engineering backgrounds in healthcare, health policy, pharmaceutical development, as well as data science with the knowledge to critically evaluate and use these technologies.

Co-author: Geoffrey Angus

Contributing Editors:

Mars Huang

Jin Long

Shannon Crawford

Oge Marques

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.

What's inside

Syllabus

Why machine learning in healthcare?

Concepts and Principles of machine learning in healthcare part 1

Concepts and Principles of machine learning in healthcare part 2

Evaluation and Metrics for machine learning in healthcare

Strategies and Challenges in Machine Learning in Healthcare

Best practices, teams, and launching your machine learning journey

Foundation models (Optional Content)

Course Conclusion

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches machine learning concepts and principles, which are useful for understanding healthcare applications

Suitable for healthcare professionals and non-engineers with limited machine learning background

Covers a range of topics relevant to machine learning in healthcare, including evaluation metrics and real-world challenges

Provides strategies for designing, building, and evaluating machine learning applications in healthcare

Taught by instructors with expertise in healthcare and machine learning

Jointly accredited for continuing education by multiple healthcare organizations

Reviews summary

Fundamentals of machine learning in healthcare

Learners say this course is engaging, comprehensive, and well-structured. Instructors Professor Matthew Lungren and Assistant Professor Serena Yeung are praised for their clarity, expertise, and enthusiasm. The course covers the basics of machine learning with a focus on healthcare applications and provides real-world examples and case studies to illustrate key concepts. Overall, learners recommend this course for those new to machine learning or those looking to apply machine learning in the healthcare field.

The hands-on exercises and real-world case studies were invaluable in solidifying my knowledge

"I learnt A LOT IN A SHORT SPACE OF TIME. THANK YOU TO THE TEACHERS"

"The instructors made the course fun, while going into various topics in depth."

"I really enjoyed learning from this course . Helped me increasing my knowledge and clearing my ambiguities and misconceptions regarding the AI in healthcare."

Great introductory course for Machine Learning in Healthcare.

"This course will give you the complete information that is required by a beginner."

"Excellent course with comprehensive fundamentals of machine learning in the healthcare field by instructor Matthew and Serena."

"absolutely delightful course and you can really tell that it was a labour of love for the course presenters."

As a total beginner, this was well-paced and helped me to gain knowledge about the topic.

"This was a great course, the presenters really gave a clear view about the differences which could happen when working with health related data set."

"Very interesting introductory course about ML in Healthcare, with a good introduction in the statistical key concepts to understand the way hoy ML works and things to care about to reduce errors and biases."

"I really enjoyed learning from this course . Helped me increasing my knowledge and clearing my ambiguities and misconceptions regarding the AI in healthcare."

Fantastic course! Both the professors are very enthusiastic about teaching the topic.

"Terrific course, one of my favorite in Coursera."

"They explain fairly clear of some concept, and it help me much."

"Great High level overview of essentials for Machine learning in Healthcare..."

Excellent course! Top-notch quality.

"Excellent introductory course to understand Machine Learning in the context of Healthcare delivery"

"Outstanding teaching and pacing by both professors and an excellent generalized instruction of ML for healthcare."

"The course is very good. Great content, very well structured and with key insights. The instructors are great, very clear explanations."

Delivered all it promises. Fast paces and geared to people with lots of ML knowledge.

"the language needs to be simpler."

"it is really good overview for people coming from a commercial background but it is done in a pretty fast manner such that I need to listened into videos again to appreciate the concept."

"The dedication and expertise of the instructors were truly inspiring, and their passion for the subject matter was evident in every aspect of the course."

it is more of a quick review

"The course is excellent. I really enjoyed the enthusiasm of the instructors."

"A bit too technical yet very interesting. Excellent course. Thanks!"

"Great overview to explain ML to all members of a team developing healthcare applications of AI"

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 Fundamentals of Machine Learning for Healthcare with these activities:

Review Calculus

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Brush up on your calculus skills before the course to reinforce your understanding of the fundamentals.

Browse courses on Statistical Modeling

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Review basic concepts like limits, derivatives, and integrals.
Work through practice problems to test your understanding.
Take an online quiz or test to assess your progress.

Develop a Machine Learning Infographic

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Create a visual representation of machine learning concepts to reinforce your understanding and enhance retention.

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Choose a specific machine learning topic or concept.
Gather relevant information and data.
Design and create the infographic using a tool like Canva or Piktochart.
Share your infographic with others to explain the concept.

Practice Machine Learning Algorithms

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Get hands-on experience with machine learning algorithms to solidify your understanding of their implementation.

Browse courses on Machine Learning Algorithms

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Choose a programming language and machine learning library.
Implement different supervised and unsupervised algorithms.
Test and evaluate your models on various datasets.

Two other activities

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Show all five activities

Design and build a machine learning model to predict patient outcomes using medical data

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Create a tangible application of machine learning concepts to healthcare, reinforcing your understanding and practical skills.

Browse courses on Machine Learning

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Gather and preprocess medical data
Select appropriate machine learning algorithms
Train and evaluate the model
Interpret and communicate results

Explore Open Source Machine Learning Projects

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Delve into open source machine learning projects to gain insights into practical implementations and real-world applications.

Browse courses on Machine Learning Projects

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Identify open source machine learning projects relevant to your interests.
Study the documentation and codebase of the projects.
Contribute to discussions or issue tracking on the project's platform.
Consider implementing a feature or functionality for the project.

Career center

Learners who complete Fundamentals of Machine Learning for Healthcare will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists develop models that leverage data to solve real-world problems. They clean, organize, analyze, and apply machine learning techniques to data, and translate their knowledge into actionable insights for stakeholders, including healthcare professionals. This course introduces the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will introduce you to practical applications of machine learning in healthcare, as well as best practices used in the field. This course may be useful for current or future Data Scientists who want to specialize in healthcare.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers implement, deploy, and maintain machine learning models. They design and build machine learning algorithms and systems, and work closely with Data Scientists to bring machine learning models to production. This course will introduce you to the lifecycle of building, deploying, and evaluating machine learning models in healthcare. It will also discuss best practices for designing, building, and evaluating machine learning applications in healthcare.

See salaries and explore the career path for Machine Learning Engineer

Health Data Analyst

Health Data Analysts collect, clean, and analyze data to identify trends and patterns in healthcare data. They work with healthcare professionals and stakeholders to identify and solve problems, and use their analytics skills to improve patient care. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will equip you with the skills needed to critically evaluate and use machine learning technologies to improve patient care.

See salaries and explore the career path for Health Data Analyst

Biostatistician

Biostatisticians use statistical methods to design and analyze studies, and interpret and communicate the results of those studies. They work in a variety of settings, including healthcare, pharmaceuticals, and academia. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will introduce you to statistical methods used in healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare.

See salaries and explore the career path for Biostatistician

Clinical Research Scientist

Clinical Research Scientists design and conduct clinical trials to evaluate the safety and efficacy of new drugs and treatments. They work closely with physicians and other healthcare professionals to develop and implement clinical trial protocols. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in clinical research and drug development.

See salaries and explore the career path for Clinical Research Scientist

Healthcare Consultant

Healthcare Consultants provide advice to healthcare organizations on a variety of topics, including strategic planning, operations management, and IT. They work with healthcare providers, payers, and other stakeholders to improve the quality and efficiency of healthcare delivery. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in healthcare consulting.

See salaries and explore the career path for Healthcare Consultant

Pharmaceutical Scientist

Pharmaceutical Scientists research, develop, and manufacture new drugs and treatments. They work in a variety of settings, including academia, industry, and government. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in drug discovery and development.

See salaries and explore the career path for Pharmaceutical Scientist

Medical Writer

Medical Writers create written content about medical topics for a variety of audiences, including patients, healthcare professionals, and the general public. They work in a variety of settings, including healthcare organizations, pharmaceutical companies, and medical writing agencies. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in medical writing.

See salaries and explore the career path for Medical Writer

Health Policy Analyst

Health Policy Analysts develop and evaluate policies that affect the healthcare system. They work in a variety of settings, including government, academia, and think tanks. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in health policy analysis.

See salaries and explore the career path for Health Policy Analyst

Healthcare Administrator

Healthcare Administrators manage the day-to-day operations of healthcare organizations, including hospitals, clinics, and long-term care facilities. They work closely with physicians, nurses, and other healthcare professionals to ensure the smooth and efficient delivery of patient care. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will equip you with a foundational understanding of the use of machine learning in healthcare administration.

See salaries and explore the career path for Healthcare Administrator

Nurse Informaticist

Nurse Informaticists use their knowledge of nursing and information technology to improve the delivery of patient care. They work in a variety of settings, including hospitals, clinics, and long-term care facilities. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in nursing informatics.

See salaries and explore the career path for Nurse Informaticist

Physician

Physicians diagnose and treat patients with a variety of medical conditions. They work in a variety of settings, including hospitals, clinics, and private practices. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in medical diagnosis and treatment.

See salaries and explore the career path for Physician

Pharmacist

Pharmacists dispense medications and provide advice on their use. They work in a variety of settings, including pharmacies, hospitals, and clinics. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in pharmacy.

See salaries and explore the career path for Pharmacist

Medical Librarian

Medical Librarians assist healthcare professionals and patients in finding and using health information. They work in a variety of settings, including hospitals, clinics, and academic institutions. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will help build a foundation for understanding the use of machine learning in medical librarianship.

See salaries and explore the career path for Medical Librarian

Medical Device Engineer

Medical Device Engineers design and develop medical devices, such as pacemakers, surgical instruments, and artificial limbs. They work in a variety of settings, including medical device companies and hospitals. This course will introduce you to the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. It will provide a foundational understanding of the use of machine learning in medical device design and development.

See salaries and explore the career path for Medical Device Engineer

Fundamentals of Machine Learning for Healthcare

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Reviews summary

Fundamentals of machine learning in healthcare

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