COV-Inception: COVID-19 Detection Tool Using Chest X-ray

Authors

Aswini ThotaFollow
Ololade Awodipe, Southern Methodist UniversityFollow
Rashmi Patel, Southern Methodist UniversityFollow

Abstract

Since the pandemic started, researchers have been trying to find a way to detect COVID-19 which is a cost-effective, fast, and reliable way to keep the economy viable and running. This research details how chest X-ray radiography can be utilized to detect the infection. This can be for implementation in Airports, Schools, and places of business. Currently, Chest imaging is not a first-line test for COVID-19 due to low diagnostic accuracy and confounding with other viral pneumonia. Different pre-trained algorithms were fine-tuned and applied to the images to train the model and the best model obtained was fine-tuned InceptionV3 model with an accuracy=0.9950, precision=1, recall=0.9907, AUC=0.9935, F1-Score=0.9953 with a loss=0.0989.

Recommended Citation

Thota, Aswini; Awodipe, Ololade; and Patel, Rashmi (2022) "COV-Inception: COVID-19 Detection Tool Using Chest X-ray," SMU Data Science Review: Vol. 6: No. 2, Article 7.
Available at: https://scholar.smu.edu/datasciencereview/vol6/iss2/7

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License