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Artificial Intelligence in Health COVID-19 diagnosis: FPA, k-NN, and SVM classifiers

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None. doi: 10.1007/s11547-020-01237-4
7. Fang Y, Zhang H, Xie J, et al. Sensitivity of chest CT
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Conflict of interest
8. Ng MY, Lee EY, Yang J, et al. Imaging profile of the COVID-19
The authors declare no conflicts of interest. infection: Radiologic findings and literature review. Radiol
Cardiothorac Imaging. 2020;2(1):e200034.
Author contributions doi: 10.1148/ryct.2020200034
Conceptualization: Betshrine Rachel Jibinsingh, Khanna 9. Ai T, Yang Z, Hou H, et al. Correlation of chest CT and
Nehemiah Harichandran RT-PCR testing in COVID-19 in China: A report of
Formal Analysis: Betshrine Rachel Jibinsingh 1014 cases. Thorac Imaging Radiol. 2020;296(2):E32-E40.
Investigation: Betshrine Rachel Jibinsingh, Kabilasri doi: 10.1148/radiol.2020200642
Jayakannan, Rebecca Mercy Victoria Manoharan
Methodology: Betshrine Rachel Jibinsingh, Khanna 10. Pal NR, Pal SK. A review on image segmentation techniques.
Nehemiah Harichandran, Anisha Isaac Pattern Recognit. 1993;26(9):1277-1294.
Writing – original draft: Betshrine Rachel Jibinsingh doi: 10.1016/0031-3203(93)90135-J
Writing – review & editing: Betshrine Rachel Jibinsingh, 11. Norouzi A, Rahim MS, Altameem A, et al. Medical image
Khanna Nehemiah Harichandran segmentation methods, algorithms, and applications. IETE
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Ethics approval and consent to participate
doi: 10.1080/02564602.2014.906861
Not applicable.
12. Sitanggang S, Sonang S, Yuhandri Y, Setiawan A. Image
Consent for publication transformation with lung image thresholding and
segmentation method. J RESTI (Rekayasa Sist Teknol
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Availability of data doi: 10.29207/resti.v7i2.4321
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Data used in this work are available from the corresponding Automatic Lung Segmentation in CT Images. In: IEEE
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