References:
[1] ""European Centre for Disease Prevention and Control, situation update worldwide," (Online). Available: https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases. (Accessed 22 06 2020).
[2] "Guidance and standard operating procedure: COVID-19 virus testing in NHS laboratories," (Online). Available: https://www.england.nhs.uk/coronavirus/publication/guidance-and-standard-operating-procedure-covid-19-virus-testing-in-nhs-laboratories/. (Accessed 01 05 2020).
[3] T. Ai, Z. Yang, H. Hou, C. Zhan, C. Chen, W. Lv, Q. Tao, Z. Sun and L. Xia, "Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases," Radiology, p. 200642, 2020.
[4] Y. Li, L. Yao, L. Chen, Y. Song and others, "Stability Issues of RT-PCR Testing of SARS-CoV-2 for Hospitalized Patients Clinically Diagnosed with COVID-19," Journal of Medical Virology, 2020.
[5] T. R. Group, "Roche develops new serology test to detect COVID-19 antibodies," April 2020. (Online). Available: https://www.roche.com/media/releases/med-cor-2020-04-17.htm. (Accessed 31 06 2020).
[6] The Guardian, "WHO warns that few have developed antibodies to Covid-19," 01 06 2020. (Online). Available: https://www.theguardian.com/society/2020/june/01/studies-suggest-very-few-have-had-covid-19-without-symptoms.
[7] buzzfeednews, "Two Antibody Studies Say Coronavirus Infections Are More Common Than We Think. Scientists Are Mad.," 22 05 2020. (Online). Available: https://www.buzzfeednews.com/article/stephaniemlee/coronavirus-antibody-test-santa-clara-los-angeles-stanford.
[8] G. D. Rubin, C. J. Ryerson, L. B. Haramati, N. Sverzellati, J. P. Kanne and others, "The role of chest imaging in patient management during the COVID-19 pandemic: a multinational consensus statement from the Fleischner Society," Chest, 2020.
[9] A. Nair, J. Rodrigues, S. Hare, A. Edey, A. Devaraj, J. Jacob, A. Johnstone, R. McStay, E. Denton and G. Robinson, "A British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic," Clinical Radiology, vol. 75, pp. 329--334, 2020.
[10] H. Wong, H. Y. S. Lam, A. Fong, S. T. Leung and o. Chin, "Frequency and distribution of chest radiographic findings in COVID-19 positive patients," Radiology, p. 201160, 2020.
[11] I. Castiglioni, D. Ippolito, M. Interlenghi, C. B. Monti, C. Salvatore, S. Schiaffino, A. Polidori and others, "Artificial intelligence applied on chest X-ray can aid in the diagnosis of COVID-19 infection: a first experience from Lombardy, Italy," medRxiv, 2020.
[12] E. E.-D. Hemdan, M. A. Shouman and M. E. Karar, "Covidx-net: A framework of deep learning classifiers to diagnose covid-19 in x-ray images," arXiv preprint arXiv:2003.11055, 2020.
[13] M. Ilyas, H. Rehman and A. Nait-ali, "Detection of Covid-19 From Chest X-ray Images Using Artificial Intelligence: An Early Review," arXiv preprint arXiv:2004.05436, 2020.
[14] D. Al-Karawi, S. Al-Zaidi, N. Polus and S. Jassim, "Machine Learning Analysis of Chest CT Scan Images as a Complementary Digital Test of Coronavirus (COVID-19) Patients," medRxiv, 2020.
[15] D. Camilleri and T. Prescott, "Analysing the limitations of deep learning for developmental robotics," in conference on Biomimetic and Biohybrid Systems, Springer, 2017, pp. 86--94.
[16] D. Al-Karawi, C. Landolfo, H. Du, H. Al-Assam, A. Sayasneh, D. Timmerman, T. Bourne and S. Jassim, "OC04. 04: A machine-learning algorithm to distinguish benign and malignant adnexal tumours from ultrasound images," Ultrasound in Obstetrics & Gynecology, vol. 54, pp. 9--10, 2019.
[17] D. Al-karawi, A. Sayasneh, H. Al-Assam, S. Jassim, N. Page, D. Timmerman, T. Bourne and H. Du, "An automated technique for potential differentiation of ovarian mature teratomas from other benign tumours using neural networks classification of 2D ultrasound static images: a pilot study," in Mobile Multimedia/Image Processing, Security, and Applications 2017, International Society for Optics and Photonics, 2017, p. 102210F.
[18] C. Cortes and V. Vapnik, "Support-vector networks," Machine learning, vol. 20, pp. 273--297, 1995.
[19] M. S. Nixon and A. S. Aguado, Feature extraction & image processing for computer vision, Academic Press, 2012.
[20] J. Ilonen and J.-K. a. o. Kamarainen, "Image feature localization by multiple hypothesis testing of Gabor features," IEEE Transactions on Image Processing, vol. 17, pp. 71--82, 2008.
[21] T. M. P. a. D. H. Ojala, "A comparative study of texture measures with classification based on featured distributions," Pattern recognition, Elsevier, pp. 51-59, 1996.
[22] N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR'05), vol. 1, IEEE, 2005, pp. 886--893.
[23] "https://github.com/ieee8023/covid-chestxray-dataset/tree/master/images," (Online). (Accessed 30 06 2020).
[24] "https://data.mendeley.com/datasets/rscbjbr9sj/3," (Online). (Accessed 05 04 2020).