We a good story
Quick delivery in the UK

Artificial Intelligence in Capsule Endoscopy

About Artificial Intelligence in Capsule Endoscopy

Artificial Intelligence in Capsule Endoscopy: A Gamechanger for a Groundbreaking Technique highlights the importance of Artificial Intelligence (AI) application in capsule endoscopy. AI will have a key role in the mid/long-term for gastrointestinal endoscopy and capsule endoscopy. This field is a prime area for the use of AI tools with over 50,000 images per endoscopy capsule video, making video analysis a time and resource consuming task and prone to error. With the application of AI image analysis tools (primarily Convolutional Neural Networks) we can decrease capsule endoscopy video reading time and resources and greatly benefit diagnostic accuracy and patient outcomes. In 15 chapters, this important reference provides a global and comprehensive perspective from the background information of AI, machine learning, deep learning and their implications in GI endoscopy. It showcases AI practical use in lesion detection and in relevant clinical indications (like obscure gastrointestinal bleeding and inflammatory bowel disease), and points to future applications of AI within the field.

Show more
  • Language:
  • Unknown
  • ISBN:
  • 9780323996471
  • Binding:
  • Paperback
  • Pages:
  • 296
  • Published:
  • February 20, 2023
  • Dimensions:
  • 192x18x234 mm.
  • Weight:
  • 630 g.
Delivery: 1-2 weeks
Expected delivery: December 15, 2024
Extended return policy to January 30, 2025

Description of Artificial Intelligence in Capsule Endoscopy

Artificial Intelligence in Capsule Endoscopy: A Gamechanger for a Groundbreaking Technique highlights the importance of Artificial Intelligence (AI) application in capsule endoscopy. AI will have a key role in the mid/long-term for gastrointestinal endoscopy and capsule endoscopy. This field is a prime area for the use of AI tools with over 50,000 images per endoscopy capsule video, making video analysis a time and resource consuming task and prone to error. With the application of AI image analysis tools (primarily Convolutional Neural Networks) we can decrease capsule endoscopy video reading time and resources and greatly benefit diagnostic accuracy and patient outcomes. In 15 chapters, this important reference provides a global and comprehensive perspective from the background information of AI, machine learning, deep learning and their implications in GI endoscopy. It showcases AI practical use in lesion detection and in relevant clinical indications (like obscure gastrointestinal bleeding and inflammatory bowel disease), and points to future applications of AI within the field.

User ratings of Artificial Intelligence in Capsule Endoscopy



Join thousands of book lovers

Sign up to our newsletter and receive discounts and inspiration for your next reading experience.