About this Course

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Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 1 in the

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

We recommend first completing Course 1 and 2 of the AI For Medicine Specialization.

Approx. 22 hours to complete

English

Subtitles: English

What you will learn

  • Estimate treatment effects using data from randomized control trials

  • Explore methods to interpret diagnostic and prognostic models

  • Apply natural language processing to extract information from unstructured medical data

Skills you will gain

treatment effect estimationmachine learning interpretationRandom Forestnatural language entity extractionquestion-answering

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 1 in the

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

We recommend first completing Course 1 and 2 of the AI For Medicine Specialization.

Approx. 22 hours to complete

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1

Week 1

8 hours to complete

Treatment Effect Estimation

8 hours to complete
12 videos (Total 43 min), 3 readings, 2 quizzes
12 videos
About Course 31m
Absolute risk reduction2m
Randomized control trials4m
Causal inference4m
Average treatment effect4m
Conditional average treatment effect4m
T-Learner3m
S-Learner4m
Evaluate individualized treatment effect3m
C-for-benefit2m
C-for-benefit calculation5m
3 readings
Connect with your mentors and fellow learners on Slack10m
About the automatic grader10m
How to refresh your workspace10m
1 practice exercise
Quiz: Measuring Treatment Effects30m
Week
2

Week 2

7 hours to complete

Medical Question Answering

7 hours to complete
10 videos (Total 32 min)
10 videos
Handling words with multiple meanings2m
Define the answer in a text4m
Automatic label extraction for medical imaging3m
Synonyms for labels2m
Is-a relationships for labels3m
Presence or absence of a disease2m
Evaluating label extraction1m
Precision and recall and F1 score4m
Evaluating on multiple disease categories3m
1 practice exercise
Quiz: Information Extraction with NLP30m
Week
3

Week 3

7 hours to complete

ML Interpretation

7 hours to complete
9 videos (Total 29 min), 2 readings, 2 quizzes
9 videos
Permutation method2m
Individual feature importance3m
Shapley values2m
Combining importances4m
Shapley values for all patients3m
Interpreting CNN models2m
Localization maps4m
Heat maps3m
2 readings
Acknowledgements10m
Citations10m
1 practice exercise
ML Interpretation30m

About the AI for Medicine Specialization

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 three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine. These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. If you are new to deep learning or want to get a deeper foundation of how neural networks work, we recommend taking the Deep Learning Specialization....
AI for Medicine

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.