AIMC Topic: Skin
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Sandwich Miura-Ori Enabled Large Area, Super Resolution Tactile Skin for Human-Machine Interactions.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 19, 2025
With substantial advances in materials science and electronics, flexible tactile sensors have emerged as a promising sector with extensive applications, notably in human-machine interactions. However, achieving large-area sensing with few sensing uni...
Artificial intelligence challenge of discriminating cutaneous arteritis and polyarteritis nodosa based on hematoxylin-and-eosin images of skin biopsy specimens.
Pathology, research and practice
Mar 15, 2025
Diseases that develop necrotizing vasculitis of cutaneous muscular arteries include cutaneous arteritis (CA) and polyarteritis nodosa (PAN). It is difficult to distinguish them based on skin biopsy findings alone. This study demonstrated that artific...
Skin lesion segmentation with a multiscale input fusion U-Net incorporating Res2-SE and pyramid dilated convolution.
Scientific reports
Mar 7, 2025
Skin lesion segmentation is crucial for identifying and diagnosing skin diseases. Accurate segmentation aids in identifying and localizing diseases, monitoring morphological changes, and extracting features for further diagnosis, especially in the ea...
Machine Learning Predicts Non-Preferred and Preferred Vertebrate Hosts of Tsetse Flies (Glossina spp.) Based on Skin Volatile Emission Profiles.
Journal of chemical ecology
Mar 7, 2025
Tsetse fly vectors of African trypanosomosis preferentially feed on certain vertebrates largely determined by olfactory cues they emit. Previously, we established that three skin-derived ketones including 6-methyl-5-hepten-2-one, acetophenone and ger...
Deep-Learning-Based Analysis of Electronic Skin Sensing Data.
Sensors (Basel, Switzerland)
Mar 6, 2025
E-skin is an integrated electronic system that can mimic the perceptual ability of human skin. Traditional analysis methods struggle to handle complex e-skin data, which include time series and multiple patterns, especially when dealing with intricat...
Interpretable machine learning unveils key predictors and default values in an expanded database of human in vitro dermal absorption studies with pesticides.
Regulatory toxicology and pharmacology : RTP
Mar 4, 2025
The skin is the main route of exposure to plant protection products for operators, workers, residents, and bystanders. Assessing dermal absorption is key for evaluating pesticide exposure. The initial approach to risk assessment involves using defaul...
Sustainable gelatin extraction from poultry skin-head-feet blend: An ultrasound-assisted approach.
Poultry science
Mar 4, 2025
The study investigated gelatin extraction from chicken skin-head-feet (SHF) blend using conventional and ultrasound-assisted methods with food-grade acetic and citric acids. Ultrasound pretreatment was introduced as an intervention in the extraction ...
Machine learning-based classification of spatially resolved diffuse reflectance and autofluorescence spectra acquired on human skin for actinic keratoses and skin carcinoma diagnostics aid.
Journal of biomedical optics
Mar 4, 2025
SIGNIFICANCE: The incidence of keratinocyte carcinomas (KCs) is increasing every year, making the task of developing new methods for KC early diagnosis of utmost medical and economical importance.
Bidirectional Long Short-Term Memory (BiLSTM) Neural Networks with Conjoint Fingerprints: Application in Predicting Skin-Sensitizing Agents in Natural Compounds.
Journal of chemical information and modeling
Mar 3, 2025
Skin sensitization, or allergic contact dermatitis, represents a critical end point in toxicity assessment, with profound implications for drug safety and regulatory decision-making. This study aims to develop a robust deep-learning-based quantitativ...
Segmentation of 3D OCT Images of Human Skin Using Neural Networks with U-Net Architecture.
Sovremennye tekhnologii v meditsine
Feb 28, 2025
UNLABELLED: is a comparative analysis of algorithms for segmentation of three-dimensional OCT images of human skin using neural networks based on U-Net architecture when training the model on two-dimensional and three-dimensional data.
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