AIMC Topic: Dermoscopy

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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) Jun 1, 2024
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...
Skin Neoplasms Dermoscopy Reproducibility of Results Female Melanoma Humans Middle Aged Neural Networks, Computer Deep Learning Genomics Aged Adult Male
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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) May 1, 2024
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...
Humans Neural Networks, Computer Female Deep Learning Dermoscopy Melanoma Image Interpretation, Computer-Assisted ROC Curve Sensitivity and Specificity Skin Neoplasms Male
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SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic Images.

Current medical imaging Jan 1, 2024
INTRODUCTION: This study introduces SkinLiTE, a lightweight supervised contrastive learning model tailored to enhance the detection and typification of skin lesions in dermoscopic images. The core of SkinLiTE lies in its unique integration of supervi...
Humans Skin Neoplasms Dermoscopy Skin Supervised Machine Learning Image Interpretation, Computer-Assisted
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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) Nov 1, 2023
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...
Internet Skin Diseases Humans Melanoma Skin Neoplasms Dermoscopy Deep Learning
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Unveiling the power of convolutional neural networks in melanoma diagnosis.

European journal of dermatology : EJD Oct 1, 2023
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, ...
Artificial Intelligence Skin Neoplasms Dermatologists Algorithms Dermoscopy Humans Melanoma Neural Networks, Computer
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Deep learning on reflectance confocal microscopy improves Raman spectral diagnosis of basal cell carcinoma.

Journal of biomedical optics Jun 1, 2022
SIGNIFICANCE: Raman spectroscopy (RS) provides an automated approach for assisting Mohs micrographic surgery for skin cancer diagnosis; however, the specificity of RS is limited by the high spectral similarity between tumors and normal tissues struct...
Dermoscopy Deep Learning Microscopy, Confocal Skin Neoplasms Carcinoma, Basal Cell Humans
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Melanoma Skin Cancer Detection Using Recent Deep Learning Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Melanoma is considered as one of the world's deadly cancers. This type of skin cancer will spread to other areas of the body if not detected at an early stage. Convolutional Neural Network (CNN) based classifiers are currently considered one of the m...
Neural Networks, Computer Melanoma Humans Dermoscopy Skin Neoplasms Deep Learning
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Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues.

Journal of biomedical optics Nov 1, 2020
SIGNIFICANCE: Melanoma is a deadly cancer that physicians struggle to diagnose early because they lack the knowledge to differentiate benign from malignant lesions. Deep machine learning approaches to image analysis offer promise but lack the transpa...
Humans Machine Learning Algorithms Biomarkers Melanoma Deep Learning Skin Neoplasms Cues Dermoscopy
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Deep learning-based, computer-aided classifier developed with dermoscopic images shows comparable performance to 164 dermatologists in cutaneous disease diagnosis in the Chinese population.

Chinese medical journal Sep 5, 2020
BACKGROUND: Diagnoses of Skin diseases are frequently delayed in China due to lack of dermatologists. A deep learning-based diagnosis supporting system can facilitate pre-screening patients to prioritize dermatologists' efforts. We aimed to evaluate ...
Dermoscopy Humans Dermatologists Computers Melanoma Deep Learning Skin Neoplasms China
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[Computer-assisted skin cancer diagnosis : Is it time for artificial intelligence in clinical practice?].

Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete Sep 1, 2020
BACKGROUND: Artificial intelligence (AI) is increasingly being used in medical practice. Especially in the image-based diagnosis of skin cancer, AI shows great potential. However, there is a significant discrepancy between expectations and true relev...
Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Artificial Intelligence Mass Screening Algorithms Skin Neoplasms Melanoma Dermoscopy Humans Neural Networks, Computer
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