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Pranav Rajpurkar, Bora Uyumazturk, Amirhossein Kiani, 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 three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine.

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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.

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What's inside

Three courses

AI for Medical Diagnosis

AI is transforming medicine, helping doctors diagnose patients more accurately, predict future health, and recommend better treatments. This specialization gives you practical experience in applying cutting-edge machine learning techniques to concrete problems in modern medicine.

AI for Medical Prognosis

(0 hours)
AI is transforming medicine, helping doctors diagnose and predict patient health outcomes more accurately. This course provides practical experience in applying machine learning to medical prognosis, focusing on tree-based machine learning. You'll learn to model non-linear relationships and handle missing data, a common challenge in medical data.

AI For Medical Treatment

(0 hours)
AI is transforming medical practice, enabling doctors to diagnose patients more accurately, predict future health outcomes, and recommend better treatments. This Specialization provides practical experience in applying machine learning to medical problems.

Learning objectives

  • 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

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