AI for Medicine Specialization

AI for Medicine Specialization

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

  • Model interpretation
  • Image Segmentation
  • Natural Language Extraction
  • Machine Learning
  • Time-To-Event Modeling
  • Deep Learning
  • Model Evaluation
  • Multi-Class Classification
  • Random Forest
  • Model Tuning
  • Treatment Effect Estimation
  • Machine Learning Interpretation

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. In this Specialization, you’ll gain practical experience applying machine learning to concrete problems in medicine. You’ll learn how to:

  • Diagnose diseases from x-rays and 3D MRI brain images
  • Predict patient survival rates more accurately using tree-based models
  • Estimate treatment effects on patients using data from randomized trials
  • Automate the task of labeling medical datasets using natural language processing
  • 3 Courses
  • >3 months (7 hours/week)
  • Intermediate



Pranav Rajpurkar

Pranav Rajpurkar

Computer Science, Stanford University
Amirhossein Kiani

Amirhossein Kiani

Curriculum Engineer
Product Manager, Google Health
Bora Uyumazturk

Bora Uyumazturk

Curriculum Developer
Machine Learning Engineer, Viaduct
    Eddy Shyu

    Eddy Shyu

    Senior Curriculum Developer
    Product Lead, DeepLearning.AI

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