Preliminary Text Analysis from Medical Records for TB Diagnosis Support Contribución en una conferencia

Nombre del libro

43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021

editorial

Institute of Electrical and Electronics Engineers Inc.

Thesis author

Andrés Felipe Romero Gómez
Andrés Leonardo Jutinico
Angelica Palencia
Carlos Awad
Erika Paola Vergara Vela

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.

autores

http://vivoweb.org/ontology/core#FacultyMember
Orjuela Cañón, Alvaro David

fecha de publicación

2021-11-1

Área temática

Salud y bienestar

Identificador de objeto digital (DOI)

https://doi.org/10.1109/embc46164.2021.9631006

Número Estándar Internacional de Libros (ISBN)

9781728111797

Número de páginas

4

Página inicial

2468

Última página

2471