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Pranav Rajpurkar,
Bora Uyumazturk,
and
Eddy Shyu
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
Read more
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
Read more
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
Machine learning is a powerful tool for prognosis, a branch of medicine that specializes in predicting the future health of patients. In this second course, you’ll walk through multiple examples of prognostic tasks. You’ll then use decision trees to model non-linear relationships, which are commonly observed in medical data, and apply them to predicting mortality rates more accurately. Finally, you’ll learn how to handle missing data, a key real-world challenge.
These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. This course focuses on tree-based machine learning, so a foundation in deep learning is not required for this course. However, a foundation in deep learning is highly recommended for course 1 and 3 of this specialization. You can gain a foundation in deep learning by taking the Deep Learning Specialization offered by deeplearning.ai and taught by Andrew Ng.
Register for this course and see more details by visiting:
OpenCourser.com/course/s96q7g/ai
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What's inside
Syllabus
Linear Prognostic Models
Build a linear prognostic model using logistic regression, then evaluate the model by calculating the concordance index. Finally, improve the model by adding feature interactions.
Read more
Syllabus
Linear Prognostic Models
Build a linear prognostic model using logistic regression, then evaluate the model by calculating the concordance index. Finally, improve the model by adding feature interactions.
Read more
Prognosis with Tree-based Models
Tune decision tree and random forest models to predict the risk of a disease. Evaluate the model performance using the c-index. Identify missing data and how it may alter the data distribution, then use imputation to fill in missing data, in order to improve model performance.
Survival Models and Time
This week, you will work with data where the time that a disease occurs is a variable. Instead of predicting just the 10-year risk of a disease, you will build more flexible models that can predict the 5 year, 7 year, or 10 year risk.
Build a Risk Model Using Linear and Tree-based Models
This week, you will fit a linear model, and a tree-based risk model on survival data, to customize a risk score for each patient, based on their health profile. The risk score represents the patient’s relative risk of getting a particular disease. You will then evaluate each model’s performance by implementing and using a concordance index that incorporates time to event and censored data.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds practical skills using tree-based machine learning algorithms, making it ideal for individuals with limited deep learning knowledge
Focuses on a specific domain, medicine, making it highly relevant for healthcare professionals and those seeking to specialize in medical AI
Provides practical experience in applying machine learning to solve real-world medical problems
Taught by expert instructors from top institutions, ensuring high-quality content and credibility
Assumes a foundation in deep learning, which may limit accessibility for beginners in the field
Save this course
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Reviews summary
Highly acclaimed ai for medical prognosis course
Learners say this course largely exceeds expectations, offering well-explained lectures, engaging assignments, and a clear progression from basic to advanced concepts. It delves into the practical applications of AI in medical prognosis, providing a solid foundation for those seeking to enter the field. However, some students note that the course lacks depth in AI algorithms and could benefit from more hands-on exercises.
Course starts with basic concepts and gradually moves to advanced topics.
"Excellent course! Real world data and robust models. Of particular value was the implementation of the SHAP feature interpretation algorithm as applied to ensemble models."
"This was a FANTASTIC course. I am very impressed with the quality of the lectures and the instructor. Thank you for teaching me how to deal with data and censorship :)"
"This course is well organized and have a good flow, that helps to understand all the facts."
Assignments are practical and well-designed.
"The class is very good. It help me build the knowledge in AI application in medicine."
"Very interesting and concise introduction to the foundations of a topic which can only grow and grow in importance in the future."
"The course is amazing. And practical quizzes and assignments are just perfect and up-to date with current affairs."
Course is organized and easy to follow.
"The course is well structured and have a good flow, that helps to understand all the facts."
"A well structured courses, which is very fun to go through."
"The course is as good as the AI for Medical Diagnosis. It is clear all along, very well illustrated, the notebooks are extremely well done."
Course could offer more exercises and practical examples.
"Good practice, but i want more hands-on assignment which focuses on how to build model from scratch, for example about COX model."
"I really like the way that the course is structured and that you are beginning with naive and easy solutions to come up with better ones, but sometimes it wasn't explicit enough that they where naive solutions while you were presenting them."
Course focuses on statistical and medical concepts rather than deep learning.
"The machine learning part is very basic and limited, and there are no deep learning related parts."
"This is a nice introductory course for some of the machine learning applications in medical prognosis."
"It seems to me the course is at least half about statistics, not 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 AI for Medical Prognosis with these
activities:
Complete the Coursera Deep Learning Specialization
Show steps
Completing this specialization will give you a strong foundation in deep learning, which is highly recommended for this course.
Browse courses on
Deep Learning
Show steps
-
Enroll in the Coursera Deep Learning Specialization
-
Complete the required courses and quizzes
Review linear regression and logistic regression
Show steps
Reviewing linear and logistic regression will help you refresh your understanding of these fundamental machine learning techniques, which are used in this course.
Browse courses on
Linear Regression
Show steps
-
Revisit lecture notes or textbooks on linear and logistic regression
Review Artificial Intelligence for Medicine by Pranav Rajpurkar and Bora Uyumazturk
Show steps
Reviewing this book will provide you with a foundation in the application of artificial intelligence in the medical field, which is essential for this course.
Show steps
-
Read chapters 1-3 to gain an overview of AI in medicine and machine learning
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve coding challenges on LeetCode or HackerRank
Show steps
Solving coding challenges will help you improve your programming skills and problem-solving abilities, which are essential for this course.
Browse courses on
Coding
Show steps
-
Create an account on LeetCode or HackerRank
-
Start solving coding challenges
Join a study group or discussion forum
Show steps
Joining a study group or discussion forum will allow you to connect with other students, share knowledge, and get help with difficult concepts.
Browse courses on
Collaboration
Show steps
-
Find a study group or discussion forum for this course
-
Participate in discussions and ask questions
Create a knowledge base of important concepts and equations
Show steps
Creating a knowledge base will help you organize and retain the important concepts and equations covered in this course.
Show steps
-
Create a document or spreadsheet to store important concepts and equations
-
Review the course materials and add relevant information to your knowledge base
Develop a machine learning model to predict the risk of a disease
Show steps
Developing a machine learning model will give you hands-on experience in applying the concepts learned in this course to a real-world problem.
Browse courses on
Machine Learning
Show steps
-
Choose a dataset of medical records
-
Clean and preprocess the data
-
Train and evaluate a machine learning model
Contribute to open-source machine learning projects
Show steps
Contributing to open-source projects will give you hands-on experience in applying your machine learning skills and collaborating with others.
Browse courses on
Open Source
Show steps
-
Find an open-source machine learning project to contribute to
-
Read the project documentation and contribute bug fixes or new features
Complete the Coursera Deep Learning Specialization
Show steps
Completing this specialization will give you a strong foundation in deep learning, which is highly recommended for this course.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Enroll in the Coursera Deep Learning Specialization
- Complete the required courses and quizzes
Review linear regression and logistic regression
Show steps
Reviewing linear and logistic regression will help you refresh your understanding of these fundamental machine learning techniques, which are used in this course.
Browse courses on
Linear Regression
Show steps
Show steps
Show steps
- Revisit lecture notes or textbooks on linear and logistic regression
Review Artificial Intelligence for Medicine by Pranav Rajpurkar and Bora Uyumazturk
Show steps
Reviewing this book will provide you with a foundation in the application of artificial intelligence in the medical field, which is essential for this course.
Show steps
Show steps
Show steps
- Read chapters 1-3 to gain an overview of AI in medicine and machine learning
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve coding challenges on LeetCode or HackerRank
Show steps
Solving coding challenges will help you improve your programming skills and problem-solving abilities, which are essential for this course.
Browse courses on
Coding
Show steps
Show steps
Show steps
- Create an account on LeetCode or HackerRank
- Start solving coding challenges
Join a study group or discussion forum
Show steps
Joining a study group or discussion forum will allow you to connect with other students, share knowledge, and get help with difficult concepts.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find a study group or discussion forum for this course
- Participate in discussions and ask questions
Create a knowledge base of important concepts and equations
Show steps
Creating a knowledge base will help you organize and retain the important concepts and equations covered in this course.
Show steps
Show steps
Show steps
- Create a document or spreadsheet to store important concepts and equations
- Review the course materials and add relevant information to your knowledge base
Develop a machine learning model to predict the risk of a disease
Show steps
Developing a machine learning model will give you hands-on experience in applying the concepts learned in this course to a real-world problem.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Choose a dataset of medical records
- Clean and preprocess the data
- Train and evaluate a machine learning model
Contribute to open-source machine learning projects
Show steps
Contributing to open-source projects will give you hands-on experience in applying your machine learning skills and collaborating with others.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find an open-source machine learning project to contribute to
- Read the project documentation and contribute bug fixes or new features
Career center
Learners who complete AI for Medical Prognosis will develop knowledge and skills
that may be useful to these careers:
Medical Doctor
Medical Doctor
The field of medicine is constantly evolving, and new technologies are emerging all the time. By taking this course, you will be able to learn about the latest advances in AI and how they are being used to improve patient care. This knowledge will make you a more valuable asset to your team and will help you to provide better care for your patients. Also, this course will help you develop the skills you need to apply AI to real-world medical problems.
Physician Assistant
Physician Assistant
As a Physician Assistant, you will be responsible for providing medical care to patients under the supervision of a physician. You will need to be able to diagnose and treat illnesses, order tests, interpret medical results, and perform minor surgeries. This course will help you develop the skills you need to succeed in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Healthcare Consultant
Healthcare Consultant
In this role, you will be responsible for advising healthcare organizations on how to improve their operations. You will use your analytical skills to identify problems and develop solutions. This course will help you develop the knowledge and skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Data Scientist
Data Scientist
As a Data Scientist, you will be responsible for collecting, analyzing, and interpreting data. This data can be used to improve patient care, develop new drugs, and design new medical devices. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Health Policy Analyst
Health Policy Analyst
In this role, you will be responsible for analyzing health policy and making recommendations to policymakers. You will use your research skills to identify problems and develop solutions. This course will help you develop the knowledge and skills you need to be successful in this role.
Healthcare Administrator
Healthcare Administrator
In this role, you will be responsible for managing the day-to-day operations of a healthcare organization. You will need to be able to budget, manage staff, and ensure that the organization is compliant with all applicable laws and regulations. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Clinical Research Coordinator
Clinical Research Coordinator
In this role, you will be responsible for coordinating clinical research studies. You will work with researchers to design and implement studies, and you will be responsible for collecting and analyzing data. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Health Informatics Specialist
Health Informatics Specialist
In this role, you will be responsible for designing and implementing health information systems. You will work with clinicians and other healthcare professionals to ensure that the systems meet their needs. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Medical Writer
Medical Writer
In this role, you will be responsible for writing medical content for a variety of audiences. You will work with clinicians and other healthcare professionals to develop articles, reports, and other materials. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Medical Librarian
Medical Librarian
In this role, you will be responsible for managing a medical library. You will work with patrons to find the information they need, and you will teach them how to use the library's resources. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Healthcare Lobbyist
Healthcare Lobbyist
In this role, you will be responsible for representing the interests of a healthcare organization before government agencies. You will work to influence legislation and regulations that affect the healthcare industry. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Healthcare Entrepreneur
Healthcare Entrepreneur
In this role, you will be responsible for starting and running your own healthcare business. You will need to be able to identify opportunities, develop a business plan, and raise capital. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Healthcare Advocate
Healthcare Advocate
In this role, you will be responsible for helping patients navigate the healthcare system. You will work with patients to find the resources they need, and you will advocate for their rights. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Healthcare Economist
Healthcare Economist
In this role, you will be responsible for analyzing the economic impact of healthcare policies. You will use your research skills to identify the costs and benefits of different policies, and you will make recommendations to policymakers. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
Healthcare Journalist
Healthcare Journalist
In this role, you will be responsible for writing about healthcare issues for a variety of audiences. You will work with experts to gather information, and you will write articles, reports, and other materials that inform the public about healthcare. This course will help you develop the skills you need to be successful in this role. It will also introduce you to the latest advances in AI and how they are being used to improve patient care.
For more career information including salaries, visit:
OpenCourser.com/course/s96q7g/ai
Reading list
We've selected eight 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
AI for Medical Prognosis .
Save
Provides a comprehensive overview of statistical methods for survival data analysis, including risk estimation, censored data, and time-dependent covariates.
Provides an overview of machine learning techniques used in healthcare, including case studies and best practices.
Provides an overview of artificial intelligence and machine learning techniques used in healthcare, including case studies.
Provides an overview of machine learning techniques used in healthcare, including case studies and best practices.
Provides a theoretical foundation for sparse statistical learning methods, including the lasso and its generalizations. A valuable resource for understanding the underlying principles of tree-based models.
Provides a comprehensive overview of pattern recognition and machine learning algorithms. A classic textbook in the field and a valuable reference for understanding core concepts.
Provides a practical introduction to statistical learning methods. A commonly used textbook for introductory machine learning courses.
Comprehensive reference for statistical learning methods. A classic textbook in the field and a valuable resource for advanced topics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/s96q7g/ai
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Effort
4 weeks, 4-5 hours/week
Level
Intermediate
Via
Coursera
Institution
DeepLearning.AI
Instructors
Pranav Rajpurkar
Bora Uyumazturk
Eddy Shyu
Language
English
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آذربایجان دیلی
This course belongs to a
collection
called
AI for Medicine. It's comprised of three courses:
- AI For Medical Treatment
- AI for Medical Prognosis (viewing)
- AI for Medical Diagnosis
Good to know
Builds practical skills using tree-based machine learning algorithms, making it ideal for individuals with limited deep learning knowledge
Focuses on a specific domain, medicine, making it highly relevant for healthcare professionals and those seeking to specialize in medical AI
Provides practical experience in applying machine learning to solve real-world medical problems
Taught by expert instructors from top institutions, ensuring high-quality content and credibility
Assumes a foundation in deep learning, which may limit accessibility for beginners in the field
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