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Updated: Jul 16, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Evaluation Frameworks for Clinical Foundation Models in Specific Tasks of Unstructured Medical Text Analysis: A
Laura Johana González Zazueta1, Betsaida Lariza López Covarrubias1, Christian Xavier Navarro Cota2
1Maestría y Doctorado en Ciencias e Ingeniería (MyDCI), Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Carretera Transpeninsular 3917, Playitas, Ensenada 22860, Baja California, Mexico.
Abstract:
Background/Objectives: Clinical foundation models (CFMs) are increasingly being applied to analyze unstructured clinical text, supporting tasks such as clinical reasoning, clinical documentation generation, and information extraction. However, their evaluation remains limited and lacks standardization, which represents a significant challenge for their safe integration into healthcare systems. This scoping review aimed to examine how performance, clinical utility, safety, and generalization are assessed in current evaluation frameworks and methodologies for CFMs applied to electronic health record text and to identify existing gaps and challenges in their evaluation. Methods: This scoping review was reported in accordance with PRISMA-ScR guidance, and the study selection process was summarized using a PRISMA flow diagram. A total of 448 records were identified in the initial search, of which 16 met the eligibility criteria and were included in the final synthesis. Results: The findings were organized into three categories: methodological frameworks, performance and clinical utility, and ethical and safety considerations. The results show progress in structured methods, evaluation schemes, and simulated environments. Nevertheless, inconsistencies persist in operational robustness, particularly regarding clinical reasoning and hallucinations. The literature also highlights important ethical concerns, including potential biases and regulatory gaps. Conclusions: Although CFMs show strong potential to transform clinical text analysis, no comprehensive framework currently guides their evaluation and safe use in real clinical settings. These findings highlight the need for a structured conceptual framework that integrates methodological, technical, clinical, and ethical criteria to support responsible implementation in clinical environments.
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