AIMC Topic: Melanoma

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Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

Clinical cancer research : an official journal of the American Association for Cancer Research Oct 21, 2019
PURPOSE: Biomarkers for disease-specific survival (DSS) in early-stage melanoma are needed to select patients for adjuvant immunotherapy and accelerate clinical trial design. We present a pathology-based computational method using a deep neural netwo...
Survival Rate Male Middle Aged Disease Progression Aged, 80 and over Young Adult Adult Area Under Curve Biopsy Neoplasm Recurrence, Local Deep Learning Image Processing, Computer-Assisted Staining and Labeling Follow-Up Studies Humans Neural Networks, Computer Algorithms Retrospective Studies Female Melanoma Risk Factors Aged
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Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms.

Journal of the European Academy of Dermatology and Venereology : JEADV Oct 8, 2019
BACKGROUND: Machine learning algorithms achieve expert-level accuracy in skin lesion classification based on clinical images. However, it is not yet shown whether these algorithms could have high accuracy when embedded in a smartphone app, where imag...
Humans Machine Learning Risk Assessment Smartphone Melanoma Mobile Applications Skin Neoplasms Diagnosis, Differential Reproducibility of Results Sensitivity and Specificity
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Dense pooling layers in fully convolutional network for skin lesion segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Oct 7, 2019
One of the essential tasks in medical image analysis is segmentation and accurate detection of borders. Lesion segmentation in skin images is an essential step in the computerized detection of skin cancer. However, many of the state-of-the-art segmen...
Humans Dermoscopy Image Interpretation, Computer-Assisted Neural Networks, Computer Melanoma Skin Neoplasms
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Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions.

JAMA network open Oct 2, 2019
IMPORTANCE: A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melanoma diagnoses throughout the patient pathway are needed to reduce the pressure on secondary care and ...
Biopsy Photography Deep Learning ROC Curve Smartphone Area Under Curve Female Melanoma Skin Neoplasms Aged Dermoscopy Humans Adult Prospective Studies Male Middle Aged
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Progressive Transfer Learning and Adversarial Domain Adaptation for Cross-Domain Skin Disease Classification.

IEEE journal of biomedical and health informatics Sep 23, 2019
Deep learning has been used to analyze and diagnose various skin diseases through medical imaging. However, recent researches show that a well-trained deep learning model may not generalize well to data from different cohorts due to domain shift. Sim...
Neural Networks, Computer Databases, Factual Melanoma Deep Learning Skin Skin Diseases Image Interpretation, Computer-Assisted Humans
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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...
Deep Learning Image Processing, Computer-Assisted Skin Humans Melanoma Melanoma, Cutaneous Malignant Skin Neoplasms Dermoscopy
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Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.

European journal of cancer (Oxford, England : 1990) Aug 14, 2019
BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer s...
Surveys and Questionnaires Diagnosis, Differential Humans Dermoscopy Hospitals, University Biopsy Neural Networks, Computer Algorithms Sensitivity and Specificity Nevus Dermatologists Male Female 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...
Mutation Skin Cell Transformation, Neoplastic Nevus, Pigmented Dermoscopy Algorithms Sensitivity and Specificity Prospective Studies Early Detection of Cancer Melanoma Humans Skin Neoplasms Artificial Intelligence
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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...
Humans Neural Networks, Computer Algorithms Melanoma Skin Neoplasms Dermoscopy Reproducibility of Results Dermatologists Surveys and Questionnaires ROC Curve Image Interpretation, Computer-Assisted Biopsy Nevus Skin
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Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction.

Journal of medical systems Jul 20, 2019
Cancer is one of the leading causes of deaths in the last two decades. It is either diagnosed malignant or benign - depending upon the severity of the infection and the current stage. The conventional methods require a detailed physical inspection by...
Image Processing, Computer-Assisted Humans Melanoma Color Neural Networks, Computer Skin Neoplasms Algorithms Dermoscopy Sensitivity and Specificity
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