AIMC Topic: Skin

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Electronic Skin: Recent Progress and Future Prospects for Skin-Attachable Devices for Health Monitoring, Robotics, and Prosthetics.

Advanced materials (Deerfield Beach, Fla.) Sep 19, 2019
Recent progress in electronic skin or e-skin research is broadly reviewed, focusing on technologies needed in three main applications: skin-attachable electronics, robotics, and prosthetics. First, since e-skin will be exposed to prolonged stresses o...
Prostheses and Implants Skin Semiconductors Biocompatible Materials Surface Properties Mechanical Phenomena Touch Wireless Technology Wound Healing Monitoring, Physiologic Robotics Polymers Humans Wearable Electronic Devices Biosensing Techniques
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Physics-driven learning of x-ray skin dose distribution in interventional procedures.

Medical physics Sep 6, 2019
PURPOSE: Radiation doses accumulated during very complicated image-guided x-ray procedures have the potential to cause stochastic, but also deterministic effects, such as skin rashes or even hair loss. To monitor and reduce radiation-related risks to...
Fluoroscopy Radiation Dosage Monte Carlo Method Uncertainty Neural Networks, Computer Machine Learning Skin
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Gabor wavelet-based deep learning for skin lesion classification.

Computers in biology and medicine Sep 4, 2019
Skin cancer cases are increasing and becoming one of the main problems worldwide. Skin cancer is known as a malignant type of skin lesion, and early detection and treatment are necessary. Malignant melanoma and seborrheic keratosis are known as commo...
Dermoscopy Deep Learning Image Processing, Computer-Assisted Skin Melanoma, Cutaneous Malignant Humans Melanoma Skin Neoplasms
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Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.

European journal of cancer (Oxford, England : 1990) Aug 8, 2019
Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30-50% of all melanomas and more than half of those in young patients evolve from initially benign lesions. Despite its...
Algorithms Skin Cell Transformation, Neoplastic Prospective Studies Nevus, Pigmented Melanoma Humans Dermoscopy Skin Neoplasms Artificial Intelligence Sensitivity and Specificity Early Detection of Cancer Mutation
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Deep neural networks are superior to dermatologists in melanoma image classification.

European journal of cancer (Oxford, England : 1990) Aug 8, 2019
BACKGROUND: Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable in classifying images of benign nevi and melanoma with dermatologist-level preci...
Dermatologists Image Interpretation, Computer-Assisted Nevus Skin Neoplasms Dermoscopy Reproducibility of Results Surveys and Questionnaires ROC Curve Biopsy Skin Humans Neural Networks, Computer Algorithms Melanoma
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Fully automated identification of skin morphology in raster-scan optoacoustic mesoscopy using artificial intelligence.

Medical physics Aug 6, 2019
PURPOSE: Identification of morphological characteristics of skin lesions is of vital importance in diagnosing diseases with dermatological manifestations. This task is often performed manually or in an automated way based on intensity level. Recently...
Humans Artificial Intelligence Female Aged Image Processing, Computer-Assisted Skin Automation Photoacoustic Techniques Aged, 80 and over Adult Male Middle Aged
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Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.

Journal of the American Academy of Dermatology Jul 12, 2019
BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain.
United States Diagnosis, Differential Skin Nevus Dermatologists Dermoscopy Spain Keratosis, Seborrheic Israel Cross-Sectional Studies International Cooperation Colombia Deep Learning Humans Internship and Residency ROC Curve Melanoma Image Interpretation, Computer-Assisted Skin Neoplasms
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Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions.

PloS one Jun 24, 2019
BACKGROUND: In recent months, multiple publications have demonstrated the use of convolutional neural networks (CNN) to classify images of skin cancer as precisely as dermatologists. However, these CNNs failed to outperform the International Symposiu...
Reproducibility of Results Databases, Factual Humans Dermatologists Deep Learning Neural Networks, Computer Melanoma Image Interpretation, Computer-Assisted Skin Algorithms Skin Neoplasms Dermoscopy
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Machine versus man in skin cancer diagnosis.

The Lancet. Oncology Jun 11, 2019
Skin Humans Algorithms Machine Learning Internet Skin Neoplasms Male
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Machine learning for the prediction of sunscreen sun protection factor and protection grade of UVA.

Experimental dermatology Jun 6, 2019
We report a prediction model for sunscreen sun protection factor (SPF) and protection grade of ultraviolet (UV) A (PA) based on machine learning. We illustrate with real clinical test results of UV protection ability of sunscreen for SPF and PA. With...
Ultraviolet Rays Reproducibility of Results Humans Materials Testing Decision Trees Machine Learning Sunscreening Agents Titanium Sun Protection Factor Skin
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