Implementation of artificial intelligence in thoracic imaging—a what, how, and why guide from the European Society of Thoracic Imaging (ESTI) - Takeaways - MDSpire

Implementation of artificial intelligence in thoracic imaging—a what, how, and why guide from the European Society of Thoracic Imaging (ESTI)

  • By

  • Fergus Gleeson

  • Marie-Pierre Revel

  • Jürgen Biederer

  • Anna Rita Larici

  • Katharina Martini

  • Thomas Frauenfelder

  • Nicholas Screaton

  • Helmut Prosch

  • Annemiek Snoeckx

  • Nicola Sverzellati

  • Benoit Ghaye

  • Anagha P. Parkar

  • February 2, 2023

  • 0 min

Share

  • 1

    Artificial intelligence (AI) mimics human brain functioning to perform complex tasks, with machine learning (ML) and deep learning (DL) as key subcategories.

  • 2

    AI shows promise in thoracic imaging, offering applications like automated lesion detection and improved diagnostic accuracy, though evidence for efficacy is still limited.

  • 3

    Despite the potential benefits of AI in radiology, acceptance remains low, particularly in lung nodule detection, where CAD tools enhance performance.

  • 4

    AI's integration into clinical workflows may lead to hybrid radiology reports combining human and AI-generated content, necessitating clear identification of AI contributions.

  • 5

    For AI to be widely adopted, it must demonstrate clinical utility and cost-effectiveness, improving workflow without adding financial burdens to healthcare.

Original Source(s)

Implementation of artificial intelligence in thoracic imaging—a what, how, and why guide from the European Society of Thoracic Imaging (ESTI)

  • by Fergus Gleeson, Marie-Pierre Revel, Jürgen Biederer, Anna Rita Larici, Katharina Martini, Thomas Frauenfelder, Nicholas Screaton, Helmut Prosch, Annemiek Snoeckx, Nicola Sverzellati, Benoit Ghaye, Anagha P. Parkar

  • February 2, 2023

Related Content

Can AI Clarify Lung Screening?

Study assesses comprehension of large language model-generated lung screening summaries

AI Falls Short on Differential Dx

New PrIME-LLM benchmark shows strong diagnostic accuracy but persistent gaps in clinical reasoning across 21 large language models

Decoding Idiopathic Intracranial Hypertension

Marc Bouffard discusses Mass General Brigham’s recently launched initiative aimed at better understanding idiopathic intracranial hypertension