[7]
Maxmen, J.S. The post-physician era: medicine in the twenty-first century; Wiley: Hoboken, 1976.
[11]
Donahue, J.; Jia, Y.; Vinyals, O.; Hoffman, J.; Zhang, N.; Tzeng, E.; Darrell, T. Decaf: a deep convolutional activation feature for generic visual recognition. ICML’14: Proceedings of the 31st International Conference on International Conference on Machine Learning, 2014 June 21 - 26 , Beijing, China 2014, pp. 647-655.
[28]
Aruna, S.; Rajagopalan, S.P.; Nandakishore, L.V. Knowledge based analysis of various statistical tools in detecting breast cancer. In: Proceedings of the First International Conference on Computer Science, Engineering and Applications (CCSEA 2011), Chennai, India, pp. 37-45. 2011 July 17,
[29]
Chaurasia, V.; Pal, S. Data mining techniques: to predict and resolve breast cancer survivability. IJCSMC, 2014, 3(1), 10-22.
[34]
Teuwen J.; van de Leemput, S.; Gubern-Mérida, A.; Rodriguez-Ruiz, A.;,Mann, R.; Bejnordi, B. Soft Tissue Lesion Detection in Mammography Using Deep Neural Networks for Object Detection. In: MIDL'18: Proceedings of the 1st Conference on Medical Imaging with Deep Learning, Amsterdam, The Netherlands. 2018; pp. 1–9.
[49]
Kohad, R.; Ahire, V. Application of machine learning techniques for the diagnosis of lung cancer with ANT colony optimization. Int. J. Comput. Appl., 2015, 113(18), 34-41.
[52]
Nasser, I.M.; Abu-Naser, S.S. Lung cancer detection using artificial neural network. Int. J. Eng. Inform. Sys., 2019, 3(3), 17-23.
[59]
Wilson, A.C.; Roelofs, R.; Stern, M.; Srebro, N.; Recht, B. The marginal value of adaptive gradient methods in machine learning. arXiv, 2017, 2017, 1705.08292.
[60]
Ruder, S An overview of gradient descent optimization algorithms arXiv, 2016, 2016, 1609.04747.
[62]
Serj, M.F.; Lavi, B.; Hoff, G.; Valls, D.P A deep convolutional neural network for lung cancer diagnostic arXiv, 2018, 1804.08170.
[64]
Chon, A.; Balachandar, N.; Lu, P. Deep convolutional neural networks for lung cancer detection; Standford University: Stanford, USA, 2017.
[67]
Zhihu, H.; Leng, J. Analysis of Hu’s moment invariants on image scaling and rotation. In: Proceedings of the 2nd International Conference on Computer Engineering and Technology, Chengdu, China, 2010, 16-18 April.
[76]
Tekade, R.; Rajeswari, K. Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, 2018 16-18 Aug.
[77]
Armato, S.G., III; McLennan, G.; Bidaut, L.; McNitt-Gray, M.F.; Meyer, C.R.; Reeves, A.P.; Zhao, B.; Aberle, D.R.; Henschke, C.I.; Hoffman, E.A.; Kazerooni, E.A.; MacMahon, H.; Van Beeke, E.J.; Yankelevitz, D.; Biancardi, A.M.; Bland, P.H.; Brown, M.S.; Engelmann, R.M.; Laderach, G.E.; Max, D.; Pais, R.C.; Qing, D.P.; Roberts, R.Y.; Smith, A.R.; Starkey, A.; Batrah, P.; Caligiuri, P.; Farooqi, A.; Gladish, G.W.; Jude, C.M.; Munden, R.F.; Petkovska, I.; Quint, L.E.; Schwartz, L.H.; Sundaram, B.; Dodd, L.E.; Fenimore, C.; Gur, D.; Petrick, N.; Freymann, J.; Kirby, J.; Hughes, B.; Casteele, A.V.; Gupte, S.; Sallamm, M.; Heath, M.D.; Kuhn, M.H.; Dharaiya, E.; Burns, R.; Fryd, D.S.; Salganicoff, M.; Anand, V.; Shreter, U.; Vastagh, S.; Croft, B.Y. The lung image database consortium (LIDC) and image database resource initiative (IDRI): A completed reference database of lung nodules on CT scans.
Med. Phys., 2011,
38(2), 915-931.
[
http://dx.doi.org/10.1118/1.3528204] [PMID:
21452728]
[107]
Ramya, V.J.; Navarajan, J.; Prathipa, R.; Kumar, L.A. Detection of melanoma skin cancer using digital camera images. ARPN J. Eng. Appl. Sci., 2015, 10(7), 3082-3085.
[108]
Al-amri, S.S.; Kalyankar, N.V.; Khamitkar, S.D. Linear and non-linear contrast enhancement image. Int. J. Comput. Sci. Netw., 2010, 10(2), 139-143.