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cc-by-nc-nd (c) Sergi Cantón Simó, 2023
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/215452

Automated clinical coding of medical notes into the SNOMED CT Medical terminology structuring system

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Automated clinical coding is the computational process of annotating healthcare free-text data by detecting relevant medical concepts and linking them to a structured medical terminology system. One of the most significant of these systems is SNOMED CT, which contains a vast array of specific medical terms, each identified by a unique ID. This work focuses on the automatic clinical coding of medical notes within the SNOMED CT system. The study presents a comprehensive review of state-of-the-art methods in this field, followed by a detailed examination of two specific approaches, each tested and their results discussed. The first method employs a classical dictionary-based approach, while the second utilizes a deep learning BERT-based model. Additionally, the work introduces a novel contribution to one of these methods and demonstrates a practical application where automatic clinical coding facilitates the extraction of specific numerical values from medical discharge summaries.

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Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona. Curs: 2023-2024. Tutor: Lauro Sumoy Van Dyck i Laura Igual Muñoz

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CANTÓN SIMÓ, Sergi. Automated clinical coding of medical notes into the SNOMED CT Medical terminology structuring system. [consulta: 7 de desembre de 2025]. [Disponible a: https://hdl.handle.net/2445/215452]

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