Accesso libero

Patient Prediction Through Convolutional Neural Networks

INFORMAZIONI SU QUESTO ARTICOLO

Cita

[1] National Heart Lung and Blood Institute, “Pneumonia.” [Online]. Available: https://www.nhlbi.nih.gov/health/pneumonia/ Search in Google Scholar

[2] “Who director-general’s opening remarks at the media briefing on [Online]. Available: https://www.who.int/director-general/speeches/detail/who-director-generals-opening-remarks-at-the-media-briefing-oncovid-19—11-march-2020/ Search in Google Scholar

[3] W. Wang et al., “Detection of sars-cov-2 in different types of clinical specimens,” vol. 323, no. 18, pp. 1843–1844, 2020. Search in Google Scholar

[4] M. E. H. Chowdhury, T. Rahman, A. Khan-dakar, R. Mazhar, M. A. Kadir, Z. B. Mahbub, K. R. Islam, M. S. Khan, A. Iqbal, N. A. Emadi, M. B. I. Reaz, and M. T. Islam, “Can ai help in screening viral and covid-19 pneumonia?” IEEE Access, vol. 8, pp. 132 665–132 676, 2020.10.1109/ACCESS.2020.3010287 Search in Google Scholar

[5] C.-J. Hsiao, E. Hing, and J. Ashman, “Trends in electronic health record system use among office-based physicians: United states, 2007-2012,” vol. 75, pp. 1–18, 2014. Search in Google Scholar

[6] V. Chouhan, S. K. Singh, A. Khamparia, D. Gupta, P. Tiwari, C. Moreira, R. Damaševičius, and V. H. C. De Albuquerque, “A novel transfer learning based approach for pneumonia detection in chest x-ray images,” Applied Sciences, vol. 10, no. 2, p. 559, 2020.10.3390/app10020559 Search in Google Scholar

[7] D. Gershgorn, “The data that transformed ai research—and possibly the world,” Quartz, July, vol. 26, pp. 2013–2017, 2017. Search in Google Scholar

[8] P. Rajpurkar, J. Irvin, R. L. Ball, K. Zhu, B. Yang, H. Mehta, T. Duan, D. Ding, A. Bagul, C. P. Langlotz et al., “Deep learning for chest radiograph diagnosis: A retrospective comparison of the chexnext algorithm to practicing radiologists,” PLoS medicine, vol. 15, no. 11, p. e1002686, 2018.10.1371/journal.pmed.1002686624567630457988 Search in Google Scholar

[9] P. Lakhani and B. Sundaram, “Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks,” Radiology, vol. 284, no. 2, pp. 574–582, 2017.10.1148/radiol.201716232628436741 Search in Google Scholar

[10] E. H. Chowdhury et al., “Covid-19 chest x-ray database.” [Online]. Available: https://www.kaggle.com/tawsifurrahman/covid19-radiography-database Search in Google Scholar

[11] J. Ker, L. Wang, J. Rao, and T. Lim, “Deep learning applications in medical image analysis,” Ieee Access, vol. 6, pp. 9375–9389, 2017. Search in Google Scholar

[12] G. Maguolo and L. Nanni, “A critic evaluation of methods for covid-19 automatic detection from x-ray images,” Information Fusion, vol. 76, pp. 1–7, 2021.10.1016/j.inffus.2021.04.008808623333967656 Search in Google Scholar

[13] E. Tartaglione, C. A. Barbano, C. Berzovini, M. Calandri, and M. Grangetto, “Unveiling covid-19 from chest x-ray with deep learning: a hurdles race with small data,” International Journal of Environmental Research and Public Health, vol. 17, no. 18, p. 6933, 2020.10.3390/ijerph17186933755772332971995 Search in Google Scholar

[14] S. Albawi, T. A. Mohammed, and S. Al-Zawi, “Understanding of a convolutional neural network,” in 2017 international conference on engineering and technology (ICET). Ieee, 2017, pp. 1–6.10.1109/ICEngTechnol.2017.8308186 Search in Google Scholar

[15] A. M. Tahir, M. E. Chowdhury, A. Khan-dakar, S. Al-Hamouz, M. Abdalla, S. Awadallah, M. B. I. Reaz, and N. Al-Emadi, “A systematic approach to the design and characterization of a smart insole for detecting vertical ground reaction force (vgrf) in gait analysis,” Sensors, vol. 20, no. 4, p. 957, 2020.10.3390/s20040957707075932053914 Search in Google Scholar

[16] M. E. Chowdhury, K. Alzoubi, A. Khan-dakar, R. Khallifa, R. Abouhasera, S. Koubaa, R. Ahmed, and A. Hasan, “Wearable real-time heart attack detection and warning system to reduce road accidents,” Sensors, vol. 19, no. 12, p. 2780, 2019.10.3390/s19122780663202131226858 Search in Google Scholar

[17] M. E. Chowdhury, A. Khandakar, K. Alzoubi, S. Mansoor, A. M Tahir, M. B. I. Reaz, and N. Al-Emadi, “Real-time smart-digital stethoscope system for heart diseases monitoring,” Sensors, vol. 19, no. 12, p. 2781, 2019.10.3390/s19122781663069431226869 Search in Google Scholar

[18] K. Kallianos, J. Mongan, S. Antani, T. Henry, A. Taylor, J. Abuya, and M. Kohli, “How far have we come? artificial intelligence for chest radiograph interpretation,” Clinical radiology, vol. 74, no. 5, pp. 338–345, 2019.10.1016/j.crad.2018.12.01530704666 Search in Google Scholar

[19] M. Dahmani, M. E. Chowdhury, A. Khan-dakar, T. Rahman, K. Al-Jayyousi, A. Hefny, and S. Kiranyaz, “An intelligent and low-cost eye-tracking system for motorized wheelchair control,” Sensors, vol. 20, no. 14, p. 3936, 2020.10.3390/s20143936741200232679779 Search in Google Scholar

[20] T. Rahman, M. E. Chowdhury, A. Khandakar, K. R. Islam, K. F. Islam, Z. B. Mahbub, M. A. Kadir, and S. Kashem, “Transfer learning with deep convolutional neural network (cnn) for pneumonia detection using chest x-ray,” Applied Sciences, vol. 10, no. 9, p. 3233, 2020.10.3390/app10093233 Search in Google Scholar

[21] G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. Van Der Laak, B. Van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Medical image analysis, vol. 42, pp. 60–88, 2017.10.1016/j.media.2017.07.005 Search in Google Scholar

[22] H. Wang, Z. Lei, X. Zhang, B. Zhou, and J. Peng, “Machine learning basics,” Deep learning, pp. 98–164, 2016. Search in Google Scholar

[23] W. S. McCulloch and W. Pitts, “A logical calculus of the ideas immanent in nervous activity,” The bulletin of mathematical biophysics, vol. 5, no. 4, pp. 115–133, 1943.10.1007/BF02478259 Search in Google Scholar

[24] F. Rosenblatt, “The perceptron: a probabilistic model for information storage and organization in the brain.” Psychological review, vol. 65, no. 6, p. 386, 1958.10.1037/h0042519 Search in Google Scholar

[25] D. H. Hubel and T. N. Wiesel, “Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex,” The Journal of physiology, vol. 160, no. 1, p. 106, 1962.10.1113/jphysiol.1962.sp006837 Search in Google Scholar

[26] Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel, “Backpropagation applied to handwritten zip code recognition,” Neural computation, vol. 1, no. 4, pp. 541–551, 1989.10.1162/neco.1989.1.4.541 Search in Google Scholar

[27] P. Mooney, “Chest x-ray images (pneumonia).” [Online]. Available: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia Search in Google Scholar

[28] “X-ray images,” https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia, accessed: 2022-01-01. Search in Google Scholar

[29] “X-ray images,” https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia, accessed: 2022-01-01. Search in Google Scholar