Developing the Digital Lung: From First Lung CT to Clinical AI

Developing the Digital Lung: From First Lung CT to Clinical AI

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Developing the Digital Lung: From First Lung CT to Clinical AI

By John D. Newell MD FACR
Reflecting recent major advances in the field of artificial intelligence, Developing the Digital Lung, From First Lung CT to Clinical AI, by Dr. John Newell, is your go-to reference for all aspects of applied artificial intelligence in lung disease development, including application to clinical medicine. It provides a unique overview of the field, beginning with a review of the origins of artificial intelligence in the mid-1970s and progressing to its application to clinical medicine in the early 2020s. Organized based on the four stages of development, this practical, easy-to-use resource helps you effectively apply artificial intelligences to lung imaging.

Developing the Digital Lung, From First Lung CT to Clinical AI is a groundbreaking book by Dr. John Newell that delves deep into the world of artificial intelligence (AI) and its application in diagnosing and treating lung diseases. With recent advancements in AI technology, this comprehensive guide explores the journey of AI in the field of lung disease development, from its origins in the 1970s to its present-day applications in clinical medicine.

Dr. Newell’s book is a must-have reference for anyone interested in understanding and utilizing AI in lung imaging. It offers a unique overview of this rapidly evolving field, providing insights into its historical development and cutting-edge innovations. The book is organized into four stages of development, making it easy to comprehend and implement AI techniques in lung imaging effectively.

One of the significant contributions of this book is its focus on precise quantitative CT of diffuse lung disease through the use of applied AI. This enables faster and more accurate diagnosis of patients with lung diseases. By tracing the development of this technology, Dr. Newell highlights the immense potential AI holds in revolutionizing the field of lung imaging. As a result, clinicians and researchers can leverage AI algorithms to produce measures of various lung conditions, including emphysema, air trapping, airway wall thickening in COPD patients, and pulmonary fibrosis and traction bronchiectasis in idiopathic pulmonary fibrosis (IPF).

Developing the Digital Lung also explores the role of different CT manufacturers, models, and scanning protocols in creating 3D digital maps of the lungs. This comprehensive understanding allows healthcare professionals to make informed decisions when selecting imaging tools and techniques. Additionally, the book provides a detailed comparison between reactive machine AI and limited memory AI methods, helping readers grasp the nuances of AI algorithms used in lung imaging.

The practical nature of this book is further enhanced through comprehensive case studies that showcase real-world applications of AI in lung imaging. These case studies illustrate how AI technology can improve the accuracy and efficiency of diagnosing and monitoring lung diseases. Furthermore, the book covers the latest advancements in cloud computing, showcasing how it can be leveraged in the field of lung imaging.

As an added bonus, the book includes an eBook version that provides readers with convenient access to the entire content. This digital format allows for easy navigation, searching, and customization of the text, figures, and references. It also offers features like note-taking, highlighting, and the ability to have the content read aloud.

About the Author

John D. Newell MD FACR is a renowned expert in the field of radiology and lung imaging. With years of experience and numerous accolades to his name, Dr. Newell brings a wealth of knowledge to this book. His expertise and passion for AI and lung imaging are evident in the comprehensive and thorough exploration of the subject matter.

Whether you are a healthcare professional, researcher, or AI enthusiast, Developing the Digital Lung, From First Lung CT to Clinical AI is an essential resource that will expand your understanding of AI in lung disease development. Dr. John Newell’s expertise and the book’s practical approach make it a valuable tool for both beginners and experienced professionals in the field. By embracing the potential of AI, you can enhance the accuracy and efficiency of diagnosing and treating lung diseases.

Order your copy today

By ordering a copy of Developing the Digital Lung, you are gaining access to groundbreaking insights and cutting-edge research in the field of AI and lung imaging. Dr. Newell’s comprehensive exploration of the subject matter will empower you to harness the power of AI in diagnosing and treating lung diseases effectively. Don’t miss out on this opportunity to stay ahead in the rapidly evolving field of AI in medicine. Place your order today and take your understanding of lung imaging to new heights!

Product Details

  • Traces the development of precise quantitative CT of diffuse lung disease through the use of applied AI, leading to faster effective diagnosis of patients with lung disease.
  • Reviews CT manufacturers, models and scanning protocol used to produce the 3D digital maps of the lungs.
  • Discusses how the data processed by AI algorithms can produce measures of emphysema, air trapping, and airway wall thickening in subjects with COPD and measures of pulmonary fibrosis and traction bronchiectasis in idiopathic pulmonary fibrosis (IPF).
  • Demonstrates the differences between reactive machine AI and limited memory AI methods.
  • Includes comprehensive case studies and current information on cloud computing.
  • An eBook version is included with purchase. The eBook allows you to access all of the text, figures and references, with the ability to search, customize your content, make notes and highlights, and have content read aloud.
  • Publisher ‏ : ‎ Elsevier; 1st edition (January 3, 2023)
  • Language ‏ : ‎ English
  • ‏ : ‎ 160 pages
  • ISBN-10 ‏ : ‎ 0323795013
  • ISBN-13 ‏ : ‎ 978-0323795012

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