AIMC Topic: Skin Neoplasms
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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...
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...
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...
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...
Deep learning data augmentation for Raman spectroscopy cancer tissue classification.
Scientific reports
Dec 13, 2021
Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular biochemical changes between cancerous vs. normal tissues and cells. In order to design...
Deep Learning-Based Transfer Learning for Classification of Skin Cancer.
Sensors (Basel, Switzerland)
Dec 6, 2021
One of the major health concerns for human society is skin cancer. When the pigments producing skin color turn carcinogenic, this disease gets contracted. A skin cancer diagnosis is a challenging process for dermatologists as many skin cancer pigment...
Robotic Extended Ultrasound-Guided Distal Pancreatectomy for Pancreatic Metastases from Uveal Melanoma.
Annals of surgical oncology
Nov 27, 2021
BACKGROUND: Isolated pancreatic metastasis from melanoma is extremely uncommon and accounts for approximately only 2% of visceral disseminations of melanoma. Interestingly, pancreatic localizations disproportionately derive from primary ocular melano...
Multi-features extraction based on deep learning for skin lesion classification.
Tissue & cell
Nov 25, 2021
For various forms of skin lesion, many different feature extraction methods have been investigated so far. Indeed, feature extraction is a crucial step in machine learning processes. In general, we can distinct handcrafted and deep learning features....
Artificial Intelligence for Skin Cancer Detection: Scoping Review.
Journal of medical Internet research
Nov 24, 2021
BACKGROUND: Skin cancer is the most common cancer type affecting humans. Traditional skin cancer diagnosis methods are costly, require a professional physician, and take time. Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tool...
A disease network-based deep learning approach for characterizing melanoma.
International journal of cancer
Nov 17, 2021
Multiple types of genomic variations are present in cutaneous melanoma and some of the genomic features may have an impact on the prognosis of the disease. The access to genomics data via public repositories such as The Cancer Genome Atlas (TCGA) all...
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