Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providing a conceptual introduction to machine learning alongside a practical guide to developing and evaluating predictive algorithms using freely-available open source software and public domain data.

Chapter Contents:

• Prologue
• 11.1 Why does medicine need AI and why are radiologists leading the forefront?
• 11.2 Basics of artificial intelligence
• 11.3 Problem identification
• 11.4 Data collection
• 11.5 Data labeling
• 11.6 Validation
• 11.7 Deployment and integration
• References

Inspec keywords: medical computing; learning (artificial intelligence)

Other keywords: medicine; medical clinicians; public domain data; medical researchers; machine learning techniques; freely-available open source software; predictive algorithms; artificial intelligence

Subjects: Biology and medical computing; Knowledge engineering techniques