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Data Semantics Modeling on a Merise Conceptual Model for Improving Artificial Intelligence Models and Clinical Decision Making

Year: 2025

Type: article

Abstract: The integration of data semantics into MERISE conceptual models offers a significant opportunity for the improvement of artificial intelligence systems applied to clinical decision making. This paper explores a systematic approach for data modeling by considering their intrinsic meaning and constraints, in order to optimize the performance of AI models and improve diagnostic accuracy.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14965856

Authors: Dr. Roch Corneille Ngoubou, Pr Basile Guy Richard Bossoto, Dr. Regis Babindamana

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W6949436353

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