Artificial Intelligence for the Objective Evaluation of Acne Investigator Global Assessment.

INTRODUCTION: The evaluation of Acne using ordinal scales reflects the clinical perception of severity but has shown low reproducibility both intra- and inter-rater. In this study, we investigated if Artificial Intelligence trained on images of Acne patients could perform acne grading with high accuracy and reliabilities superior to those of expert physicians. METHODS: 479 patients with acne grading ranging from clear to severe and sampled from three ethnic groups participated in this study. Multi-polarization images of facial skin of each patient were acquired from five different angles using the visible spectrum. An Artificial Intelligence was trained using the acquired images to output automatically a measure of Acne severity in the 0-4 numerical range of the Investigator Global Assessment (IGA). RESULTS: The Artificial Intelligence recognized the IGA of a patient with an accuracy of 0.854 and a correlation between manual and automatized evaluation of r=0.958 (P less than .001). DISCUSSION: This is the first work where an Artificial Intelligence was able to directly classify acne patients according to an IGA ordinal scale with high accuracy, no human intervention and no need to count lesions. J Drugs Dermatol. 2018;17(9):1006-1009.

Olive mill wastewater reuse to enable solar photo-Fenton-like processes for the elimination of priority substances in municipal wastewater treatment plant effluents.

Olive mill wastewater (OMW) appears as an interesting and innovative natural alternative to synthetic chelating agents of iron in solar photo-Fenton processes at circumneutral pH due to its high polyphenol content, valorizing wastewater typically found in sunny countries. The aim of this work was the reuse of OMW for the elimination of other recalcitrant microcontaminants: terbutryn, chlorfenvinphos, diclofenac, and pentachlorophenol. Highly diluted OMW (1:1500) was employed to keep the iron in solution at circumneutral pH. Eighty percent degradation of microcontaminants was achieved, although the reaction rate was slow compared with conventional photo-Fenton process, due to Fe-polyphenol complex instability at neutral pH. At pH around 4 (considerable superior to the photo-Fenton optimal pH 2.8), Fe-polyphenol complex stability was promoted: solar UV energy required was 25 times lower to reach the objective of 80% microcontaminants degradation, which was attained in a single step, without coupling with other processes. Operating photo-Fenton at slightly acidic pH was proposed for the first time for possible reuse of treated wastewater in crop irrigation, requiring minimum pH adjustment by simply mixing it with natural wastewater. Graphical abstract.