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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/215452
Automated clinical coding of medical notes into the SNOMED CT Medical terminology structuring system
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Abstract
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. [consulted: 12 of June of 2026]. Available at: https://hdl.handle.net/2445/215452