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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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[Artificial Intelligence in Radiology - Definition, Potential and Challenges].

Bettina Baessler1

  • 1Institut für Diagnostische und Interventionelle Radiologie, Universitätsspital Zürich.

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Summary

Artificial Intelligence (AI) is transforming healthcare, particularly radiology, due to its digital nature. This review explores AI's current benefits and challenges in radiology.

Keywords:
Artificial IntelligenceBildgebungDeep LearningIntelligence artificielleKünstliche IntelligenzRadiologieapprentissage machineapprentissage profonddeep learningimagerieimagingmachine learningmaschinelles Lernenradiologieradiology

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Artificial Intelligence (AI) is increasingly integrated into daily life and healthcare.
  • Radiology is particularly susceptible to AI-driven changes due to digitization and technical affinity.
  • The rapid advancement of AI raises questions about its impact on established medical fields like radiology.

Purpose of the Study:

  • To define Artificial Intelligence (AI) in the context of radiology.
  • To explore the potential benefits and applications of AI in radiological practices.
  • To identify and discuss the significant challenges associated with AI implementation in radiology.

Main Methods:

  • This article is a review, synthesizing current knowledge on AI in radiology.
  • It examines the definition, capabilities, and implications of AI.
  • The review addresses both the advantages and obstacles of AI in the field.

Main Results:

  • AI is a potent force with the capacity to revolutionize radiology.
  • Current AI applications offer significant assets to radiological workflows.
  • Several major challenges impede the widespread adoption and full potential of AI in radiology.

Conclusions:

  • AI is poised to significantly alter daily routines in healthcare, especially in radiology.
  • Understanding AI's definition, potential, and challenges is crucial for radiologists.
  • Proactive engagement with AI developments is necessary for the future of radiology.