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Skin

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Diagnostic accuracy of content-based dermatoscopic image retrieval with deep classification features.

The British journal of dermatology Oct 17, 2018
BACKGROUND: Automated classification of medical images through neural networks can reach high accuracy rates but lacks interpretability.
Humans Retrospective Studies Image Processing, Computer-Assisted Skin Skin Diseases Datasets as Topic Dermoscopy Deep Learning ROC Curve
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Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

The Journal of investigative dermatology Oct 17, 2018
Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is a cost-effective approach for finding drugs that can be used to treat diseases for which they are cu...
Humans Cohort Studies ROC Curve Computational Biology Drug Repositioning Machine Learning Algorithms Transcriptome Immune System Diseases Skin Skin Diseases PubMed
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Skin surface lipid differences in sensitive skin caused by psychological stress and distinguished by support vector machine.

Journal of cosmetic dermatology Oct 2, 2018
BACKGROUND: Sensitive skin refers to skin that tends to be highly responsive to stimuli such as physical, chemical, and psychological. Psychological factors play an important role in the pathology of sensitive skin.
Hyperesthesia Chromatography, High Pressure Liquid Tandem Mass Spectrometry Permeability Young Adult Adult Stress, Psychological Discriminant Analysis Skin Humans Support Vector Machine Female Lipids
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Deep-learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumour diagnosis.

The British journal of dermatology Sep 19, 2018
BACKGROUND: Application of deep-learning technology to skin cancer classification can potentially improve the sensitivity and specificity of skin cancer screening, but the number of training images required for such a system is thought to be extremel...
Image Interpretation, Computer-Assisted Datasets as Topic Mobile Applications Skin Dermatologists Humans Skin Neoplasms Deep Learning Dermoscopy Smartphone Sensitivity and Specificity
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Diagnostic performance of real-time robotic arm-assisted F-FDG PET/CT-guided percutaneous biopsy in metabolically active abdominal and pelvic lesions.

European journal of nuclear medicine and molecular imaging Aug 30, 2018
PURPOSE: To evaluate the feasibility and diagnostic performance of F-FDG PET/CT-guided biopsy of abdominal and pelvic lesions with automated robotic arm (ARA) assistance.
Image-Guided Biopsy Skin Feasibility Studies Fluorodeoxyglucose F18 Robotics Positron Emission Tomography Computed Tomography Pelvis Young Adult Female Adult Aged Humans Male Aged, 80 and over Time Factors Middle Aged Abdomen Adolescent
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Interpretation of the Outputs of a Deep Learning Model Trained with a Skin Cancer Dataset.

The Journal of investigative dermatology Jun 1, 2018
Algorithms Skin Neoplasms Humans Deep Learning Skin
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A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks.

Computational intelligence and neuroscience May 31, 2018
Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional metho...
Image Interpretation, Computer-Assisted Wounds and Injuries Machine Learning Wound Healing Humans Skin Neural Networks, Computer
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An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine.

Computational intelligence and neuroscience May 27, 2018
Multispectral palmprint recognition system (MPRS) is an essential technology for effective human identification and verification tasks. To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE) and regularized extrem...
Male Skin Time Factors Hand Humans Image Processing, Computer-Assisted Biometric Identification Pattern Recognition, Automated Machine Learning Female
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An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images.

Medical physics May 9, 2018
PURPOSE: To develop and evaluate a new automatic classification algorithm to identify voxels containing skin, vasculature, adipose, and fibroglandular tissue in dedicated breast CT images.
Mammography Skin Breast Pattern Recognition, Automated Cluster Analysis Unsupervised Machine Learning Adipose Tissue Humans Tomography, X-Ray Computed
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Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features.

IEEE journal of biomedical and health informatics May 1, 2018
The presence of certain clinical dermoscopic features within a skin lesion may indicate melanoma, and automatically detecting these features may lead to more quantitative and reproducible diagnoses. We reformulate the task of classifying clinical der...
Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Databases, Factual Melanoma Skin Neoplasms Dermoscopy ROC Curve Skin
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