AIMC Topic: Skin Neoplasms

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Deep Learning-Based Classification for Melanoma Detection Using XceptionNet.

Journal of healthcare engineering Mar 22, 2022
Skin cancer is one of the most common types of cancer in the world, accounting for at least 40% of all cancers. Melanoma is considered as the 19th most commonly occurring cancer among the other cancers in the human society, such that about 300,000 ne...
Deep Learning Image Processing, Computer-Assisted Melanoma Skin Neoplasms Dermoscopy Humans
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Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.

Scientific reports Mar 10, 2022
In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and size of the skin lesion makes the segmentation task more challenging. Lesion segmentation is an initial step in CAD schemes as it leads to low error rat...
Skin Diseases Skin Neoplasms Dermoscopy Deep Learning Humans Neural Networks, Computer Melanoma
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Uncertainty-aware skin cancer detection: The element of doubt.

Computers in biology and medicine Mar 2, 2022
Artificial intelligence (AI)-based medical diagnosis has received huge attention due to its potential to improve and accelerate the decision-making process at the patient level in a range of healthcare settings. Despite the recent signs of progress i...
Humans Neural Networks, Computer Bayes Theorem Monte Carlo Method Uncertainty Artificial Intelligence Algorithms Skin Neoplasms
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Evaluation of Artificial Intelligence-Assisted Diagnosis of Skin Neoplasms: A Single-Center, Paralleled, Unmasked, Randomized Controlled Trial.

The Journal of investigative dermatology Feb 18, 2022
TRIAL DESIGN: This was a single-center, unmasked, paralleled, randomized controlled trial.
Algorithms Skin Neoplasms Humans Diagnosis, Differential Neural Networks, Computer Artificial Intelligence
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Deep Learning Algorithms for Predicting Breslow Thickness from Dermoscopic Images of Acral Lentiginous Melanomas.

The Journal of investigative dermatology Jan 12, 2022
Humans Skin Neoplasms Retrospective Studies Deep Learning Melanoma Melanoma, Cutaneous Malignant
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New Trends in Melanoma Detection Using Neural Networks: A Systematic Review.

Sensors (Basel, Switzerland) Jan 10, 2022
Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today. The high mortality rate associated with melanoma makes it necessary to detect the early stages to be treated urgently and properly. This is the ...
Humans Neural Networks, Computer Artificial Intelligence Melanoma Skin Neoplasms Deep Learning
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Non-invasive scoring of cellular atypia in keratinocyte cancers in 3D LC-OCT images using Deep Learning.

Scientific reports Jan 10, 2022
Diagnosis based on histopathology for skin cancer detection is today's gold standard and relies on the presence or absence of biomarkers and cellular atypia. However it suffers drawbacks: it requires a strong expertise and is time-consuming. Moreover...
Histological Techniques Pathology Middle Aged Humans Deep Learning Algorithms Imaging, Three-Dimensional Female Aged, 80 and over Tomography, Optical Coherence Adult Skin Male Keratinocytes Skin Neoplasms Aged
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DUNEScan: a web server for uncertainty estimation in skin cancer detection with deep neural networks.

Scientific reports Jan 7, 2022
Recent years have seen a steep rise in the number of skin cancer detection applications. While modern advances in deep learning made possible reaching new heights in terms of classification accuracy, no publicly available skin cancer detection softwa...
Humans Decision Support Techniques Skin Neoplasms Predictive Value of Tests Internet Image Interpretation, Computer-Assisted Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Photography Uncertainty
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Perceptions of the use of artificial intelligence in the diagnosis of skin cancer: an outpatient survey.

Clinical and experimental dermatology Dec 23, 2021
BACKGROUND: Convolutional neural networks (artificial intelligence, AI) are rapidly appearing within the field of dermatology, with diagnostic accuracy matching that of dermatologists. As technologies become available for use by both the health profe...
Adult Humans Attitude to Health Cross-Sectional Studies Artificial Intelligence Male Female Aged, 80 and over Health Surveys Skin Neoplasms Young Adult Age Factors Middle Aged Aged Patient Acceptance of Health Care Diagnosis, Computer-Assisted Adolescent
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Machine Learning and Its Application in Skin Cancer.

International journal of environmental research and public health Dec 20, 2021
Artificial intelligence (AI) has wide applications in healthcare, including dermatology. Machine learning (ML) is a subfield of AI involving statistical models and algorithms that can progressively learn from data to predict the characteristics of ne...
Humans Artificial Intelligence Skin Neoplasms Machine Learning Neural Networks, Computer Algorithms
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