Can I read Implementing Deep Learning Algorithms in Anatomic Pathology Using Open-source Deep Learning Libraries on EtoBox?

Implementing Deep Learning Algorithms in Anatomic Pathology Using Open-source Deep Learning Libraries by Ewen McAlpine; Pamela Michelow is a Medicine article available to read on EtoBox.

What is Implementing Deep Learning Algorithms in Anatomic Pathology Using Open-source Deep Learning Libraries about?

The application of artificial intelligence technologies to anatomic pathology has the potential to transform the practice of pathology, but, despite this, many pathologists are unfamiliar with how these models are created, trained, and evaluated. In addition, many pathologists may feel that they do not possess the necessary skills to allow them to embark on research into this field. This article aims to act as an introductory tutorial to illustrate how to create, train, and evaluate simple artificial learning models (neural networks) on histopathology data sets in the programming language Python using the popular freely available, open-source libraries Keras, TensorFlow, PyTorch, and Detecto. Furthermore, it aims to introduce pathologists to commonly used terms and concepts used in artificial intelligence.

Who reads Implementing Deep Learning Algorithms in Anatomic Pathology Using Open-source Deep Learning Libraries?

Author

Ewen McAlpine; Pamela Michelow

Publisher

Lippincott Williams and Wilkins; Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins; Lippincott Williams & Wilkins Ltd.; Ovid Technologies (Wolters Kluwer Health) (ISSN 1072-4109)

Published

2020

Language

EN

Field

Medicine (Health Sciences)