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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Artificial Intelligence Enabling Radiology Reporting.

Bernardo C Bizzo1, Renata R Almeida2, Tarik K Alkasab1

  • 1Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Founders 210, Boston, MA 02114, USA.

Radiologic Clinics of North America
|October 25, 2021
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) tools are enhancing radiology reporting by using structured data for consistency and tracking. Radiologists will review AI-generated data, improving report accessibility and integration into patient care pathways.

Keywords:
Artificial intelligenceDeep learningIntegrationMachine learningRadiologyReportStructured

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Area of Science:

  • Radiology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • The radiology reporting process is evolving to include structured, semantically labeled data.
  • Artificial intelligence (AI) offers potential for improving internal report consistency and longitudinal tracking.

Purpose of the Study:

  • To explore the application of AI tools in structured radiology reporting.
  • To enhance the value and integration of radiology reports into patient care pathways.

Main Methods:

  • Utilizing AI technologies within a structured reporting framework.
  • Assembling to-do lists of relevant issues by AI, incorporating patient history.
  • Radiologists reviewing and selecting AI-generated data for electronic health record (EHR) transmission.

Main Results:

  • AI tools can assist with internal report consistency and longitudinal tracking.
  • AI can generate relevant issue lists by incorporating patient history.
  • Radiologist feedback is crucial for ongoing AI tool improvement.

Conclusions:

  • Structured reporting with AI enhances report accessibility and integration into care pathways.
  • AI-powered tools promise to increase the value of radiology reports.