Prediction system of erythemas for phototypes I and II, using deep-learning

Keywords: Erythema, photo-type, ultraviolet index, prediction, artificial intelligence

Abstract

Background: The sun is a natural source of electromagnetic radiation, upon which are found the ultraviolet (UV) rays, where only the types A and B are able to irradiate over the surface of the Earth in different proportions. Although the sun helps human skin in the formation of vitamin D, the mineralization of bones, and absorption of calcium and phosphorus in the organism, it can cause damage on the skin by prolonged exposure to UV radiation, generating adverse effects on human health like erythema formation, photo-toxicity, photo-allergy, idiopathic lesions, and photo-dermatitis, among others. This paper, shows the results of developing a prediction system of the exposure time of a person to UV rays coming from the sun, which can cause erythema on human skin, using the standards in UV index and the dose limits of radiation allowed for phototypes I and II, aiming to foresee the generation of these kind of lesions. This was made by the implementation of artificial intelligence algorithms like Deep Belief Networks and Backpropagation, based in the Deep Learning technique. These algorithms use as training parameters for the neural network, the meteorological data such as the sky clearness index, the radiation on the horizontal surface and average air temperature, supplied by the National Aeronautics and Space Administration (NASA). With the data, a neural network aiming to foresee the UV index for the following year of the data input was trained, in addition some mathematical regressions were applied allowing in this way, to obtain an approach to the behavior of the UV index along the day. Likewise, this information was used to estimate the maximum time of sun exposure, for the period of time contained between 6:00 a.m. and 6:00 p.m. This paper, also presents some conclusions based in the results found, which try to establish some important considerations in order to implement the neural networks.

|Abstract
= 80 veces | PDF
= 87 veces|

Downloads

Download data is not yet available.

Author Biographies

Juan Felipe PUERTA BARRERA, Universidad Militar Nueva Granada

Virtual Applications Group-GAV, Mechatronics Engineer

Dario AMAYA HURTADO, Universidad Militar Nueva Granada

Doctor in Mechanical Engineering. Mechatronics Engineering Program.

Robinson JÍMENEZ MORENO, Universidad Militar Nueva Granada

Virtual Applications Group-GAV, Mechatronic Engineer

References

de Paula Corrêa. Algoritmos Para Cálculos De Transferência Radiativa Na Região Ultravioleta Do Espectro Eletromagnético. Informative. Cachoeira Paulista – SP: Centro De Previsão De Tempo E Estudos Climáticos, Divisão de Satélites e Sistemas Ambientais; 2005.

Calle A, Perez A, Casanova J. Calculo De Mapas De Irradiancia Eritematica A Partir De Datos De Ozono Toms Sobre La Totalidad De La Peninsula Iberica. In VIII Congreso Nacional De Teledetección; 1999; Albacete, España: VIII Congreso Nacional De Teledeteccion. 166-169 p.

Allen R, Suurmond D, Wolff K. Fitzpatrick, Atlas En Color Y Sinopsis De Dermatología Clínica Vienna, Austria: Mc Graw Hill; 2008.

Goldsmith L, Katz S, Gilchrest B, Paller A, Leffell D, Wolff K. Fitzpatrick Dermatologia En Medicina General Álvarez J, Carini F, Facorro Lea, editors. Madrid, Spain: Editorial Médica Panamericana S.A; 2008.

Amini N, Matthews J, Dabiri F, Vahdatpour A, Noshadi H, Sarrafzadeh M. A Wireless Embedded Device For Personalized Ultraviolet Monitoring. Los Angeles, California, USA: University of California, Computer Science Department; 2012.

Na S, Baek S, Park JK, Park Jh. Daily Global Solar Radiation Estimate In The South Korea Based On Geostationary Satellite Remote Sensing. In International Geoscience and Remote Sensing Symposium; 2012; Cungbuk: IEEE. 7460 - 7463 p.

Agencia De Protección Ambiental De Los Estados Unidos. United States Environmental Protection Agency. [Internet]. Washington, DC; 2001 [cited 2014 10 20]. Available in: HYPERLINK“http://www.epa.gov/sunwise/doc/sunuvu_spanish.pdf” http://www.epa.gov/sunwise/doc/sunuvu_spanish.pdf .

Organizacion Mundial De La Salud. Global Solar UV Index: A Practical Guide. Ginebra, Suiza: World Health Organization publications; 2003.

Linares A, Ruiz J, et al. Generation Of Synthetic Daily Global Solar Radiation Data Based On ERA-Interim. Energy. 2011 August; 36(8): 5356–5365 p.

Bendekhis M, Benghanem A. Artificial Neural Network Model for Prediction Solar Radiation Data: Application for Sizing Stand-alone Photovoltaic Power System. In Power Engineering Society General Meeting, 2005. IEEE; 2005; Algiers, Algeria: IEEE. 40 - 44 p.

Lu J, Manton J, Kazmierczak E, Sinclair R. Erythema Detection In Digital Skin Images. In 2010 17th IEEE International Conference on Image Processing (ICIP); 2010; Hong Kong, China: IEEE 17th International Conference on Image Processing. 2545 - 2548 p.

Ahmand MH, Ihtatho D, et al. Objective Assessment Of Psoriasis Erythema For PASI Scoring. J. Med. Eng. Technol. 2009 September; 33(7).

Hani A, Nugroho H, Asirvadam V. Implementation Of Fuzzy C-Means Clustering For Psoariasis Assessment On Lesion Erythema. In Industrial Electronics and Applications (ISIEA); 2012; Bandung, Indonesia: IEEE Symposium on Industrial Electronics and Applications (ISIEA2012). p. 331-334.

National Aeronautics And Space Administration. Prediction Of Worldwide Energy Resource. [Internet]. [cited 2014 10 20]. Available in: HYPERLINK “http://power.larc.nasa.gov/” http://power.larc.nasa.gov/ .

Goldsmith L, Wolff K, Katz S, Paller A, Leffell D, Gilchrest B, et al. Fitzpatrick’s Dermatology in General Medicine New York: Mc Graw Hill; 2012.

Sachdeva S. Fitzpatrick Skin Typing: Applications In Dermatology. Indian J Dermatol Venereol Leprol. 2008; 75(1): 93-96 p

Published
2016-05-01
How to Cite
PUERTA BARRERA J. F., AMAYA HURTADO D., & JÍMENEZ MORENO R. (2016). Prediction system of erythemas for phototypes I and II, using deep-learning. Vitae, 22(3), 188-196. https://doi.org/10.17533/udea.vitae.v22n3a03
Section
Pharmacology and Toxicology