LetterModification of the nail psoriasis severity index
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Nail psoriasis severity index: a useful tool for evaluation of nail psoriasis
J Am Acad Dermatol
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Cited by (52)
A mask R-CNN based automatic assessment system for nail psoriasis severity
2022, Computers in Biology and MedicineCitation Excerpt :Convolutional deep neural network (CNN) performs promisingly in object recognition and image classification [8]. Mask R-CNN [9]; an extension on faster Region-based CNN (R-CNN), allows efficient object detection in image and generate segmentation mask for each instance at the same time. Connected to a Feature Pyramid Network (FPN) and a ResNet101 backbone, Mask R-CNN uses ResNet101 architecture to extract features from the input image and a regional proposal network (RPN) to predicts if the object is present in that region.
Improvement of 11 patients with nail psoriasis with apremilast: Results of an investigator-initiated open-label study
2020, Journal of the American Academy of DermatologyEfficacy and safety of Indigo naturalis extract in oil (Lindioil) in treating nail psoriasis: A randomized, observer-blind, vehicle-controlled trial
2014, PhytomedicineCitation Excerpt :Consequently, the mtNAPSI was used to measure the severity of psoriasis in the nail matrix and nail bed for the most severely affected nail. Each nail quadrant was scored from 0 (no sign) to 3 (severe involvement), providing a maximum score of 96 (Parrish et al. 2005). The subject global assessment (SGA) and physician global assessment (PGA) were performed at week 12 to measure the improvement of nail psoriasis.
Transungual Drug Delivery System for the Topical Treatment of Onychomycosis: A Review
2022, Drug Delivery Letters