Post-acne hyperpigmentation: Evaluation of risk factors and the use of artificial neural network as a predictive classifier

Firas Al-Qarqaz; Khaldon Bodoor; Ala Baba; Ali Al-Yousef; Jihan Muhaidat; Diala Alshiyab

doi:10.4081/dr.2021.8223

Post-acne hyperpigmentation: Evaluation of risk factors and the use of artificial neural network as a predictive classifier

Dermatol Reports. 2021 Oct 6;13(3):8223. doi: 10.4081/dr.2021.8223. eCollection 2021 Nov 17.

Authors

Firas Al-Qarqaz¹, Khaldon Bodoor², Ala Baba¹, Ali Al-Yousef³, Jihan Muhaidat¹, Diala Alshiyab¹

Affiliations

¹ Department of Dermatology, Jordan University of Science and Technology, Irbid.
² Department of Biotechnology and Genetic Engineering, Faculty of Science, Jordan University of Science and Technology, Irbid.
³ Computer Department, Computer and Information Technology College, Jerash University, Jerash, Jordan.

Abstract

Acne is common among young individuals. People with dark skin have a higher risk for developing pigmentary complications. Inflammation is an important factor in post-acne hyperpigmentation however other factors are also involved in developing this complication however these factors are not well studied. The aim of this study is to identify risk factors involved in post-acne hyperpigmentation. Clinical data related to acne, acne- related hyperpigmentation were collected. Data was analyzed for risk factors associated with acne pigmentation. Artificial neural network was used as predictive disease classifier for the outcome of pigmentation. Majority of patients in this study (339 patients) had dark skin phototypes (3 and 4). Post- acne hyperpigmentation was seen in more than 80% of patients. Females, darker skin color, severe acne, facial sites, and excessive sunlight exposure, squeezing or scratching lesions are important risk factors for post-acne hyperpigmentation. Post-acne hyperpigmentation is multifactorial. Several factors implicated in PAH are modifiable by adequate patient education (lesion trauma, excessive sunlight exposure). The use of ANN was helpful in predicting appearance of post-acne hyperpigmentation based on identified risk factors.

Keywords: Acne; Artificial neural network; Classification; Post-acne hyperpigmentation.

Grants and funding

Funding and ethical approval: The study was supported and approved by the deanship of research at Jordan University of Science and Technology number 2018-0207. The study was approved by the ethical committee (IRB number: 164-2018).