AI for Medical Prognosis
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and...
By Pranav Rajpurkar on Coursera
About This Course
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.
Topics Covered
Frequently Asked Questions
How much does AI for Medical Prognosis cost?
Visit the AI for Medical Prognosis course page for current pricing and available discounts.
Who teaches AI for Medical Prognosis ?
AI for Medical Prognosis is taught by Pranav Rajpurkar, DeepLearning.AI.
What skill level is AI for Medical Prognosis for?
This course is designed for advanced learners.
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