AIMC Topic: Skin Diseases

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Deep learning-based skin care product recommendation: A focus on cosmetic ingredient analysis and facial skin conditions.

Journal of cosmetic dermatology
BACKGROUND: Recommendations for cosmetics are gaining popularity, but they are not being made with consideration of the analysis of cosmetic ingredients, which customers consider important when selecting cosmetics.

LAMA: Lesion-Aware Mixup Augmentation for Skin Lesion Segmentation.

Journal of imaging informatics in medicine
Deep learning can exceed dermatologists' diagnostic accuracy in experimental image environments. However, inaccurate segmentation of images with multiple skin lesions can be seen with current methods. Thus, information present in multiple-lesion imag...

Deep learning-aided decision support for diagnosis of skin disease across skin tones.

Nature medicine
Although advances in deep learning systems for image-based medical diagnosis demonstrate their potential to augment clinical decision-making, the effectiveness of physician-machine partnerships remains an open question, in part because physicians and...

DBNet-SI: Dual branch network of shift window attention and inception structure for skin lesion segmentation.

Computers in biology and medicine
The U-shaped convolutional neural network (CNN) has attained remarkable achievements in the segmentation of skin lesion. However, given the inherent locality of convolution, this architecture cannot capture long-range pixel dependencies and multiscal...

Understanding skin color bias in deep learning-based skin lesion segmentation.

Computer methods and programs in biomedicine
BACKGROUND: The field of dermatological image analysis using deep neural networks includes the semantic segmentation of skin lesions, pivotal for lesion analysis, pathology inference, and diagnoses. While biases in neural network-based dermatoscopic ...

A Narrative Review: Opportunities and Challenges in Artificial Intelligence Skin Image Analyses Using Total Body Photography.

The Journal of investigative dermatology
Artificial intelligence (AI) algorithms for skin lesion classification have reported accuracy at par with and even outperformance of expert dermatologists in experimental settings. However, the majority of algorithms do not represent real-world clini...

Revolutionizing diagnostic pathology: The emergence and impact of artificial intelligence-what doesn't kill you makes you stronger?

Clinics in dermatology
This study explored the integration and impact of artificial intelligence (AI) in diagnostic pathology, particularly dermatopathology, assessing its challenges and potential solutions for global health care enhancement. A comprehensive literature sea...

Dermatology and artificial intelligence.

Clinics in dermatology
Artificial Intelligence (AI) is a very powerful new tool that is destined to markedly advance many areas of dermatology, including cosmetic dermatology, oculoplastics, cancer detection and treatment, dermatopathlogy, and identification of pathogens. ...