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MELANOMA DIAGNOSIS USING CONVOLUTIONAL NEURAL NETWORKS OF DEEP LEARNING

DOI: https://doi.org/10.29296/25877305-2018-06-06
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Issue: 
6
Year: 
2018

A. Melerzanov, Candidate of Medical Sciences; D. Gavrilov, Candidate of Technical Sciences Moscow Institute of Physics and Technology (State University)

The paper gives the skin disease classification system by photographs, which has been developed using the algorithms based on convolutional neural networks of deep learning. The method allows the automated diagnosis of skin tumors with at least 91% accuracy.

Keywords: 
oncology
deep convolutional neural networks
melanoma diagnosis
computer vision
telemedicine



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References: 
  1. Fradkin C.Z., Zalutskij I.V. Melanoma kozhi / Minsk: Belarus', 2000; 221 s.
  2. Snarskaja E.S., Molochkov V.A. Bazalioma / M.: Meditsina, 2003; 136 s.
  3. Haratishvili T.K., Tjuljandin S.A., Hatyrev S.A. Vozmozhnosti lechenija mestnorasprostranennogo raka kozhi // Vopr. onkologii. – 2005; 51 (3): 385–7.
  4. Institute N. Surveillance, Epidemiology, and End Results (SEER). Program Cancer Statistics Review, 1975–2013 [Electronic resource] / SEER, 2015.
  5. Erdei E., Torres S. A new understanding in the epidemiology of melanoma // Exp. Rev. Anticancer Ther. – 2010; 10 (11): 1811–23.
  6. Filippi A., Fava P., Badellino S. et al. Radiotherapy and immune checkpoints inhibitors for advanced melanoma // Radiother. Oncol. – 2012; 120 (1): 1–12.
  7. Survival Rates for Melanoma Skin Cancer, by Stage. [Electronic resource]. URL: https://www.cancer.org/cancer/melanoma-skin-cancer/detection-diagnosis-staging/survival-rates-for-melanoma-skin-cancer-by-stage.html
  8. Berwick M., Begg C., Fine J. et al. Screening for cutaneous melanoma by skin self-examination // J. Natl. Cancer Inst. – 1996; 88 (1): 17–23.
  9. De Giorgi V., Grazzini M., Rossari S. et al. Is skin self-examination for cutaneous melanoma detection still adequate? A retrospective study // Dermatology. – 2012; 225 (1): 1–6.
  10. Malishevskaja N.P., Sokolova A.V. Sovremennye metody neinvazivnoj diagnostiki melanomy kozhi // Vestn. dermatol. i venerol. – 2014; 4: 46–53.
  11. Gavrilov D. Artifical intelligence-Al image recognition for helthcare. 16 AMWC. Monaco, 2018; p. 84–5.
  12. Torrey L., Shavlik J. Transfer Learning. Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques / IGI Global, 2009; 242–64 p.
  13. Shlens J. Train your own image classifier with Inception in TensorFlow [Electronic resource]. 2016. URL: https://research.googleblog.com/2016/03/train-your-own-image-classifier-with.html (accessed: 24.01.2018).