Introduction to AI & Machine Learning in Healthcare from edX

This course introduces you to how Artificial Intelligence (AI) and Machine Learning (ML) can be used to improve healthcare. This is the first course of a two course program. In this self-paced course, you'll be introduced to the fundamentals of AI and ML. The concepts, theories, and principles are tied to real-world healthcare applications and examples. Learn how these technologies enhance clinical and operational decision-making, while exploring the core principles of artificial intelligence and machine learning. Engage in current debates and discussions to understand the latest AI trends in healthcare. Stay updated with cutting-edge research as you discover how AI is transforming the future of healthcare. This course is suitable for anyone who wants to gain a solid foundation in AI and ML and its important implications within healthcare settings.

The course is comprised of 5 modules that you should complete in order, as each subsequent module builds on the previous one.

Module 1: Overview of AI and its Impact on Healthcare
Module 2: AI Legal and Ethical Considerations including Privacy Concerns
Module 3: Basics of Data & Healthcare
Module 4: Basic Machine Learning Algorithms
Module 5: Case Studies of AI & ML in Healthcare

What's inside

Learning objectives

By the end of this course, you will be able to:
Define ai and ml terminology and concepts while also understanding their transformative impact on healthcare.
Explore the legal, ethical, and privacy implications of implementing ai in healthcare.

Describe the fundamentals of healthcare data and its significance in ai applications.
Describe fundamental machine learning algorithms and their applications in healthcare.

By the end of this course, you will be able to:
Define ai and ml terminology and concepts while also understanding their transformative impact on healthcare.
Explore the legal, ethical, and privacy implications of implementing ai in healthcare.
Describe the fundamentals of healthcare data and its significance in ai applications.
Describe fundamental machine learning algorithms and their applications in healthcare.

Syllabus

Course time commitment

2-4 hours per module (10-20 hours total)

Grading and certificate

Verified Learners can earn a certificate for this course by scoring at least 80% overall on the course assessments.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores the transformative impact of AI and ML on healthcare, which is highly relevant for professionals seeking to innovate and improve patient outcomes

Examines legal, ethical, and privacy implications of AI in healthcare, which is essential for responsible development and deployment of these technologies

Uses real-world healthcare applications and examples to illustrate AI and ML concepts, which helps learners understand practical uses

Requires completion of modules in order, as each subsequent module builds on the previous one, which may not suit all learning styles

Requires a score of at least 80% overall on the course assessments to earn a certificate, which may be a barrier for some learners

Presented by MGH Institute of Health Professions, which is known for its contributions to healthcare education and research

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 AI & Machine Learning in Healthcare with these activities:

Review Basic Statistics

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Reinforce your understanding of basic statistical concepts, which are foundational for understanding machine learning algorithms.

Browse courses on Basic Statistics

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Review key statistical concepts like mean, median, mode, standard deviation, and distributions.
Practice solving basic statistical problems.

Review 'Healthcare Data Analytics'

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Gain a deeper understanding of healthcare data analytics, which is essential for applying AI and ML effectively in healthcare settings.

View Putting Knowledge to Work on Amazon

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Read the chapters related to data sources and data quality in healthcare.
Summarize the key challenges and opportunities in healthcare data analytics.

Discuss Ethical Implications of AI in Healthcare

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Deepen your understanding of the ethical considerations surrounding AI in healthcare through collaborative discussion and debate.

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Form a study group with other learners.
Choose a specific ethical dilemma related to AI in healthcare.
Research different perspectives on the dilemma.
Discuss the pros and cons of each perspective.

Four other activities

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Create a Presentation on AI Case Studies

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Solidify your understanding of AI applications in healthcare by researching and presenting real-world case studies.

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Select 2-3 case studies of AI/ML in healthcare from Module 5 or external sources.
Research the details of each case study, including the problem, solution, and results.
Create a presentation summarizing each case study.
Present your findings to your peers or instructor.

Review 'Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again'

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Gain a broader perspective on the potential of AI to transform healthcare and enhance the doctor-patient relationship.

View Deep Medicine: How Artificial Intelligence Can... on Amazon

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Read the book, focusing on the chapters related to the impact of AI on the doctor-patient relationship.
Reflect on how AI can be used to enhance, rather than replace, human interaction in healthcare.

Develop a Simple AI-Powered Diagnostic Tool

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Apply your knowledge of machine learning algorithms to develop a practical AI-powered diagnostic tool for a specific healthcare application.

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Choose a specific healthcare problem that can be addressed with AI diagnostics.
Gather relevant data for training your model.
Select and implement a suitable machine learning algorithm.
Evaluate the performance of your diagnostic tool.

Compile a List of AI/ML Resources for Healthcare

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Create a valuable resource for yourself and others by compiling a list of relevant AI/ML tools, datasets, and research papers in healthcare.

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Search for publicly available datasets related to healthcare.
Identify relevant AI/ML tools and libraries.
Compile a list of influential research papers in the field.
Organize your findings into a shareable document.

Career center

Learners who complete Introduction to AI & Machine Learning in Healthcare will develop knowledge and skills that may be useful to these careers:

Healthcare Data Analyst

A Healthcare Data Analyst works with patient data to identify trends and improve healthcare outcomes. This course helps build a foundation in the fundamentals of data and its application in healthcare. With the knowledge gained, you will be able to analyze healthcare datasets and provide insights for clinical and operational decision making. The course's focus on legal and ethical considerations, as well as privacy concerns, makes it particularly helpful for those working with sensitive patient information. This course may be useful for those who seek a career as a Healthcare Data Analyst.

See salaries and explore the career path for Healthcare Data Analyst

Clinical Informatics Specialist

A Clinical Informatics Specialist works to improve healthcare delivery through information technology that helps to ensure secure data collection and storage. Through this course, specialists will learn how AI and machine learning can enhance clinical decision making, and they will be able to engage with current debates and discussions about these cutting edge trends. This course may be useful for those interested in becoming a Clinical Informatics Specialist as it introduces the legal and ethical implications of AI in healthcare, which is a vital component of this role's responsibilities.

See salaries and explore the career path for Clinical Informatics Specialist

Artificial Intelligence Researcher

Artificial Intelligence Researchers investigate the capabilities of artificial intelligence and machine learning with a focus on improving efficiency. This course introduces the fundamentals of artificial intelligence and machine learning. The course also presents the latest research in the field, especially as it relates to healthcare. This course may be useful for anyone who wants to become an Artificial Intelligence Researcher, as they will need a strong foundational knowledge of the concepts, theories and principles taught in the course.

See salaries and explore the career path for Artificial Intelligence Researcher

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. Through this course you will learn about basic machine learning algorithms, and how they can apply to healthcare. The course also uses case studies to provide real world examples of machine learning in healthcare settings, making it highly valuable. This course may be useful for anyone who seeks to develop a career as a Machine Learning Engineer, particularly in healthcare related applications.

See salaries and explore the career path for Machine Learning Engineer

Healthcare Consultant

Healthcare Consultants leverage their knowledge of healthcare delivery and policy to advise healthcare organizations on improving their operations and quality of service. Through this course, you will learn how AI and machine learning are being used to enhance clinical and operational decision making, and will participate in discussions about healthcare trends. A Healthcare Consultant will be prepared to make more informed recommendations by taking this course, especially if they work with healthcare providers who are considering implementing AI and machine learning.

See salaries and explore the career path for Healthcare Consultant

Medical Software Developer

Medical Software Developers create programs for medical devices, applications, and systems. This course introduces machine learning concepts and algorithms, providing developers with a foundation in the principles of AI, especially as they apply to clinical settings. Learning about the ethical and privacy considerations unique to medical technology, as provided by this course, is also valuable to a Medical Software Developer. This course may be useful for anyone who seeks to create AI-powered solutions for the medical field.

See salaries and explore the career path for Medical Software Developer

Health Technology Product Manager

A Product Manager in health technology guides the development and marketing of health technology products and services. This course introduces the fundamentals of AI and ML and explores their impact on healthcare. Gaining familiarity with how these technologies can be applied to products can assist a Health Technology Product Manager in identifying new trends, and opportunities for innovation. This is especially true with the course's focus on real world applications and examples, which will be valuable to anyone interested in becoming a Health Technology Product Manager.

See salaries and explore the career path for Health Technology Product Manager

Health Informatics Analyst

A Health Informatics Analyst works with healthcare data, systems, and technologies. This course introduces the fundamentals of AI and ML and ties them to real-world healthcare applications. It also covers the legal and ethical considerations of using AI in healthcare, as well as data privacy concerns. This course provides a basic background in how to work with data in ways that are both effective and responsible. This course may be useful for those interested in a career as a Health Informatics Analyst.

See salaries and explore the career path for Health Informatics Analyst

Public Health Analyst

A Public Health Analyst examines data to evaluate programs and policies, and recommends changes. With a focus on data and its significance to the field of healthcare, this course can inform a Public Health Analyst about how AI and machine learning can improve the quality of healthcare. The course's discussion of research can also be applicable to the analyst's responsibility to implement evidence-based practices. This course may be useful for anyone who wants to pursue a career as a Public Health Analyst.

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Biostatistician

A Biostatistician applies statistical methods to biological, medical and public health data. A focus on healthcare data helps the biostatistician to perform analysis to identify critical trends and patterns, and to better predict outcomes. By working with data through the lens of artificial intelligence and machine learning, this course can help a Biostatistician develop new techniques for applying their skills. This course is beneficial for anyone who is a Biostatistician interested in using these techniques in this dynamic field.

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Medical Device Engineer

A Medical Device Engineer designs and develops medical devices, often in combination with aspects software, and must be aware of ethical considerations. This course introduces AI concepts and technologies, which can be integrated into medical devices. By studying case studies where AI and ML are used in healthcare, as provided by this course, a Medical Device Engineer will be able to more successfully develop new technologies. This course may be useful for anyone interested in this field.

See salaries and explore the career path for Medical Device Engineer

Medical Writer

A medical writer produces documentation about medical products, devices, and research, and it is helpful to understand how new technologies are changing the field. By taking this course and familiarizing themselves with the latest trends in artificial intelligence and machine learning, a Medical Writer will be able to report on these developments more accurately. A Medical Writer may find this course beneficial when writing about AI and machine learning applications in healthcare.

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Regulatory Affairs Specialist

A Regulatory Affairs Specialist ensures that products comply with the law. A course that focuses on legal and ethical considerations, such as this one, may help the Regulatory Affairs Specialist as they navigate compliance of healthcare technology. The course's focus on AI and machine learning allows a Regulatory Affairs Specialist to stay up-to-date on these innovations. This course may be useful for a Regulatory Affairs Specialist who is involved in technology.

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Research Scientist

Research Scientists design and conduct research studies for the purpose of creating knowledge. This course may be useful for a Research Scientist as it introduces the most recent investigations into artificial intelligence and machine learning, especially with respect to healthcare. The coursework will help a Research Scientist understand the methodology of these fields, and how they can be applied to healthcare. This course may be helpful for a Research Scientist.

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Quality Improvement Specialist

A Quality Improvement Specialist works to improve the quality of care and safety within healthcare organizations. By learning the fundamentals of AI and machine learning through this course, a Quality Improvement Specialist will be able to better understand the impact of these technologies on healthcare. This course may be helpful for a Quality Improvement Specialist who wants to implement AI and machine learning in the service of better patient outcomes.

See salaries and explore the career path for Quality Improvement Specialist

Introduction to AI & Machine Learning in Healthcare

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