Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/215452
Title: Automated clinical coding of medical notes into the SNOMED CT Medical terminology structuring system
Author: Cantón Simó, Sergi
Director/Tutor: Sumoy Van Dyck, Lauro
Igual Muñoz, Laura
Keywords: Llenguatge mèdic
Glossaris
Informàtica mèdica
Treballs de fi de màster
Aprenentatge automàtic
Medical language
Glossaries
Medical informatics
Master's thesis
Machine learning
Issue Date: 1-Sep-2024
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.
Note: 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
URI: https://hdl.handle.net/2445/215452
Appears in Collections:Màster Oficial - Fonaments de la Ciència de Dades
Programari - Treballs de l'alumnat

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