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

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Published on: July 11, 2025

[Artificial intelligence: Guidelines for internists].

K Gratzer¹, H Servy¹, L Chiche²

¹E-health Services Sanoïa, 188, avenue 2nd DB, 13420 Gémenos, France.

La Revue De Medecine Interne

|January 4, 2020

Summary

This summary is machine-generated.

Big data and artificial intelligence offer significant opportunities in medicine, from diagnostics to real-time analysis. Guidelines are essential for their responsible development and application in internal medicine, particularly in Europe.

Keywords:

Affections musculosquelettiques Artificial intelligence Big data Intelligence artificielle Internal medicine Machine learning Médecine interne Rheumatic and musculoskeletal diseases

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Area of Science:

Medical Informatics
Data Science
Artificial Intelligence in Medicine

Background:

The proliferation of open data and connected devices fuels rapid advancements in big data and artificial intelligence.
These technologies present numerous opportunities within medicine, including enhanced diagnostics and real-time statistical analysis.

Purpose of the Study:

To clarify the concepts of big data and artificial intelligence and their interrelations.
To provide an overview of European progress in applying these technologies to internal medicine.

Main Methods:

Conceptual clarification of big data and artificial intelligence.
Literature review and synthesis of European-level progress in medical applications.

Main Results:

Established clear definitions and correlations between big data and artificial intelligence.
Documented the current state and advancements of these technologies in the European medical field.

Conclusions:

Guidelines and recommendations are crucial for the ethical and effective integration of big data and AI in internal medicine.
The European landscape shows significant, rapidly expanding progress in this domain.