Events MOL2NET'21, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 7th ed.

Event submissions

Published

This submission belongs to the session 05. AI.MED-08: AI, Neuro Sciences, Med. Info., & Biomed. Eng. Congress, Coruña, Spain-Carleton, Canada-Stanford, USA, 2021 of the event MOL2NET'21, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 7th ed.

Published date

21 Feb, 2021

Citation

Nuria Pereira Espasandín, David Maseda Neira, Diana Marcela Noriega Cobo, Iago Iglesias Corrás, Alejandro Pazos, Julián Dorado, Cristian Robert Munteanu, COVID-19 prediction using chest X-ray medical images and Deep Learning, in Proceedings of MOL2NET'21, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 7th ed., 25 January–30 December 2021, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-07-09260

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COVID-19 prediction using chest X-ray medical images and Deep Learning

Nuria Pereira Espasandín ¹

David Maseda Neira ¹

Diana Marcela Noriega Cobo ¹

Iago Iglesias Corrás ¹

Alejandro Pazos ^1,2,3

Julián Dorado ^1,2

Cristian Robert Munteanu ^1,2,3

1. Computer Science Faculty, University of Coruña, 15071 A Coruña, Spain

2. Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC), Campus de Elviña s/n 15071 A Coruña, Spain

3. Biomedical Research Institute of A Coruña (INIBIC), University Hospital Complex of A Coruña (CHUAC), 15006, A Coruña, Spain

Abstract

The current project is proposing a simple, fast and free solution to predict COVID-19 using a chest X-ray image as inputs and python scripts with deep learning from Fastai package. This is a prototype classifier to be improved and implemented as Web and mobile apps.

Keywords

COVID-19

chest X-Ray image

predict

deep learning

Manuscript

manuscript_DL-COVID19(MOL2NET21).pdf

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