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Melanoma

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Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.

Experimental dermatology
This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE2...

A novel deep learning framework for accurate melanoma diagnosis integrating imaging and genomic data for improved patient outcomes.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate in the advanced stages. Therefore, early and accurate detection of melanoma plays an important role in improving patients' prognosis. Biopsy is the tra...

Comprehensive analysis of clinical images contributions for melanoma classification using convolutional neural networks.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Timely diagnosis plays a critical role in determining melanoma prognosis, prompting the development of deep learning models to aid clinicians. Questions persist regarding the efficacy of clinical images alone or in conjunction with dermos...

Deep learning approach for skin melanoma and benign classification using empirical wavelet decomposition.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Melanoma is a malignant skin cancer that causes high mortality. Early detection of melanoma can save patients' lives. The features of the skin lesion images can be extracted using computer techniques to differentiate early between melanom...

[MOCK MOLE: PRODUCING SYNTHETIC IMAGES THAT RECAPITULATE CONFOCAL PATTERNS OF MELANOCYTIC NEVI VIA DEEP-LEARNING MODELS].

Harefuah
INTRODUCTION: Melanocytic nevi present microscopic patterns, which differ in their associated melanoma risk, and can be non-invasively recognized under Reflectance Confocal Microscopy (RCM).

Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
INTRODUCTION: Particularly within the Internet of Medical Things (IoMT) context, skin lesion analysis is critical for precise diagnosis. To improve the accuracy and efficiency of skin lesion analysis, CAD systems play a crucial role. To segment and c...

Unveiling the power of convolutional neural networks in melanoma diagnosis.

European journal of dermatology : EJD
Convolutional neural networks are a type of deep learning algorithm. They are mostly applied in visual recognition and can be used for the identification of melanomas. Multiple studies have evaluated the performance of convolutional neural networks, ...

[Deep learning-based fully automated intelligent and precise diagnosis for melanocytic lesions].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Melanocytic lesions occur on the surface of the skin, in which the malignant type is melanoma with a high fatality rate, seriously endangering human health. The histopathological analysis is the gold standard for diagnosis of melanocytic lesions. In ...

Machine learning for the identification of decision boundaries during the transition from radial to vertical growth phase superficial spreading melanomas.

Melanoma research
The objective of this study was to compute threshold values for the diameter of superficial spreading melanomas (SSMs) at which the radial growth phase (RGP) evolves into an invasive vertical growth phase (VGP). We examined reports from 1995 to 2019 ...