Preliminary Text Analysis from Medical Records for TB Diagnosis Support

Andres Felipe Romero Gomez, Alvaro D. Orjuela-Canon, Andres L. Jutinico, Carlos Awad, Erika Vergara, Angelica Palencia

Producción científica: Capítulo en Libro/ReporteContribución a la conferencia

Resumen

Tuberculosis is an infectious disease that is spread through the air from one person to another and is one of the top ten causes of death in the world according to the World Health Organization. From biomedical engineering, decision support systems based on artificial intelligence have shown advantages for healthcare personnel in tasks such as diagnosis and screening. A specific area of the artificial intelligence is the natural language processing, however, most of these approaches are based on available data. This paper shows the construction of a dataset based on medical records of subjects suspected of tuberculosis. In addition, an initial exploration of the contents of the constructed dataset and how this approach can be followed by a natural language processing to support tuberculosis diagnosis in data demanding scenarios are presented.Clinical Relevance - In some developing countries as Colombia, it is difficult to develop systems based on artificial intelligence due to the availability of data. This proposal holds a strategy to build a dataset to train machine learning models, and to obtain support diagnosis tools, employing natural language from the medical scenario from text written by health professionals in the medical record. In this way, trained models based on this information available can be employed in places where medical infrastructure is precarious.

Idioma originalInglés estadounidense
Título de la publicación alojada43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas2468-2471
Número de páginas4
Edición2021
ISBN (versión digital)9781728111797
DOI
EstadoPublicada - nov. 2021
Evento43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, México
Duración: nov. 1 2021nov. 5 2021

Serie de la publicación

NombreProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (versión impresa)1557-170X

Conferencia

Conferencia43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
País/TerritorioMéxico
CiudadVirtual, Online
Período11/1/2111/5/21

Áreas temáticas de ASJC Scopus

  • Procesamiento de senales
  • Ingeniería biomédica
  • Visión artificial y reconocimiento de patrones
  • Informática aplicada a la salud

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