Skin Research and Technology

Papers
(The H4-Index of Skin Research and Technology is 14. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Effect of face mask on skin characteristics changes during the COVID‐19 pandemic62
Skin measurement devices to assess skin quality: A systematic review on reliability and validity27
Influence of quarantine mask use on skin characteristics: One of the changes in our life caused by the COVID‐19 pandemic21
Comparison of reflectance confocal microscopy and line‐field optical coherence tomography for the identification of keratinocyte skin tumours20
Elastic Fibres in the subcutaneous tissue: Is there a difference between superficial and muscular fascia? A cadaver study20
Characterization of skin aging through high‐frequency ultrasound imaging as a technique for evaluating the effectiveness of anti‐aging products and procedures: A review19
Hair removal in dermoscopy images using variational autoencoders18
Japanese experiment of a complete and objective automatic grading system of facial signs from selfie pictures: Validation with dermatologists and characterization of changes due to age and sun exposur18
High‐frequency ultrasound in the diagnosis of the spectrum of cutaneous squamous cell carcinoma: Noninvasively distinguishing actinic keratosis, Bowen's Disease, and invasive squamous cell carcinoma17
High‐frequency ultrasound for differentiation between high‐risk basal cell carcinoma and cutaneous squamous cell carcinoma15
Usefulness of high‐frequency ultrasound in differentiating basal cell carcinoma from common benign pigmented skin tumors15
Ultra‐high‐frequency ultrasound monitoring of plaque psoriasis during ixekizumab treatment15
High‐frequency (22‐MHz) ultrasound for assessing the depth of basal cell carcinoma invasion15
Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things14
Automatic segmentation and melanoma detection based on color and texture features in dermoscopic images14
Aging‐related shift of eccrine sweat glands toward the skin surface due to tangling and rotation of the secretory ducts revealed by digital 3D skin reconstruction14
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