AI for Medicine
Instructors: Pranav Rajpurkar
Also available on Coursera
AI for Medicine
Intermediate
3 Courses
137 Video Lessons
21 Reading Lessons
29 Practices
9 Graded Assignments
Instructor: Pranav Rajpurkar
DeepLearning.AI
What you'll 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
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
Instructor
Frequently Asked Questions
Course Outline
40 Video Lessons • 8 Reading Lessons • 8 Practices • 3 Graded Assignments
Welcome to the Specialization with Andrew and Pranav
Video • 4 mins
Demo
Video • 1 min
Recommended Pre-requisites
Video • 1 min
Join the DeepLearning.AI Forum to ask questions, get support, or share amazing ideas!
Reading • 2 mins
Medical Image Diagnosis
Video • 2 mins
Eye Disease and Cancer Diagnosis
Video • 3 mins
Data Exploration & Image Pre-Processing
Code Example • 1 hour
Building and Training a Model for Medical Diagnosis
Video • 2 mins
Training, Prediction, and Loss
Video • 1 min
Image Classification and Class Imbalance
Video • 1 min
Binary Cross Entropy Loss Function
Video • 3 mins
Impact of Class Imbalance on Loss Calculation
Video • 3 mins
Counting Labels and Weighted Loss Function
Code Example • 1 hour
Resampling to Achieve Balanced Classes
Video • 1 min
Multi-Task
Video • 1 min
Multi-task Loss, Dataset size, and CNN Architectures
Video • 2 mins
Densenet
Code Example • 1 hour
Working with a Small Training Set
Video • 2 mins
Generating More Samples
Video • 3 mins
Model Testing
Video • 2 mins
Splitting Data by Patient
Video • 1 min
Patient Overlap & Data Leakage
Code Example • 1 hour
Sampling
Video • 2 mins
Ground Truth and Consensus Voting
Video • 1 min
Additional Medical Testing
Video • 2 mins
Disease Detection with Computer Vision
• 30 mins
(Optional) Refreshing your Workspace and Downloading your Notebook
Reading • 5 mins
Chest X-Ray Medical Diagnosis with Deep Learning
Graded・Code Assignment • 3 hours
AI for Medicine
Intermediate
3 Courses
137 Video Lessons
21 Reading Lessons
29 Practices
9 Graded Assignments
Instructor: Pranav Rajpurkar
DeepLearning.AI
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