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Skin Diseases

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Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding.

Scientific reports
This study aims to explore the efficacy of a hybrid deep learning and radiomics approach, supplemented with patient metadata, in the noninvasive dermoscopic imaging-based diagnosis of skin lesions. We analyzed dermoscopic images from the Internationa...

Deep Learning-Based Synthetic Skin Lesion Image Classification.

Studies in health technology and informatics
Advances in general-purpose computers have enabled the generation of high-quality synthetic medical images that human eyes cannot differ between real and AI-generated images. To analyse the efficacy of the generated medical images, this study propose...

Natural language processing in dermatology: A systematic literature review and state of the art.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Natural Language Processing (NLP) is a field of both computational linguistics and artificial intelligence (AI) dedicated to analysis and interpretation of human language.

Skin lesion segmentation using deep learning algorithm with ant colony optimization.

BMC medical informatics and decision making
BACKGROUND: Segmentation of skin lesions remains essential in histological diagnosis and skin cancer surveillance. Recent advances in deep learning have paved the way for greater improvements in medical imaging. The Hybrid Residual Networks (ResUNet)...

Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: The 2022 global outbreak of mpox has significantly impacted health facilities, and necessitated additional infection prevention and control measures and alterations to clinic processes. Early identification of suspected mpox cases will as...

Skinformatics: Navigating the big data landscape of dermatology.

Journal of the European Academy of Dermatology and Venereology : JEADV
Big data and associated approaches to analyse it are on the rise, especially in healthcare settings. This growth is also seen with unique applications in the field of dermatology. While big data offer a plethora of opportunity for improving our curre...

Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.

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: This report evaluates the potential of artificial intelligence (AI) in psychodermatology, emphasizing its ability to enhance diagnostic accuracy, treatment efficacy, and personalized care. Psychodermatology, which explores the connection ...

Artificial intelligence in dermatopathology: a systematic review.

Clinical and experimental dermatology
Medical research, driven by advancing technologies like artificial intelligence (AI), is transforming healthcare. Dermatology, known for its visual nature, benefits from AI, especially in dermatopathology with digitized slides. This review explores A...

Attention-Guided Learning With Feature Reconstruction for Skin Lesion Diagnosis Using Clinical and Ultrasound Images.

IEEE transactions on medical imaging
Skin lesion is one of the most common diseases, and most categories are highly similar in morphology and appearance. Deep learning models effectively reduce the variability between classes and within classes, and improve diagnostic accuracy. However,...

Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.

International journal of computer assisted radiology and surgery
PURPOSE: This study investigates the application of Radiomic features within graph neural networks (GNNs) for the classification of multiple-epitope-ligand cartography (MELC) pathology samples. It aims to enhance the diagnosis of often misdiagnosed s...