AIMC Topic: Dermoscopy

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Auditing the inference processes of medical-image classifiers by leveraging generative AI and the expertise of physicians.

Nature biomedical engineering Dec 28, 2023
The inferences of most machine-learning models powering medical artificial intelligence are difficult to interpret. Here we report a general framework for model auditing that combines insights from medical experts with a highly expressive form of exp...
Algorithms Physicians Melanoma Artificial Intelligence Machine Learning Image Processing, Computer-Assisted Skin Image Interpretation, Computer-Assisted Skin Neoplasms Dermoscopy Humans
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SkinViT: A transformer based method for Melanoma and Nonmelanoma classification.

PloS one Dec 27, 2023
Over the past few decades, skin cancer has emerged as a major global health concern. The efficacy of skin cancer treatment greatly depends upon early diagnosis and effective treatment. The automated classification of Melanoma and Nonmelanoma is quite...
Carcinoma, Basal Cell Melanoma Carcinoma, Squamous Cell Dermoscopy Humans Skin Neoplasms Artificial Intelligence
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Integrated convolutional neural network for skin cancer classification with hair and noise restoration.

Turkish journal of medical sciences Oct 16, 2023
BACKGROUND/AIM: Skin lesions are commonly diagnosed and classified using dermoscopic images. There are many artifacts visible in dermoscopic images, including hair strands, noise, bubbles, blood vessels, poor illumination, and moles. These artifacts ...
Dermoscopy Deep Learning Hair Artifacts Neural Networks, Computer Skin Neoplasms Humans
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Demonstration of Convolutional Neural Networks to Determine Patch Test Reactivity.

Dermatitis : contact, atopic, occupational, drug Sep 12, 2023
Convolutional neural networks (CNNs) have the potential to assist allergists and dermatologists in the analysis of patch tests. Such models can help reduce interprovider variability and improve consistency of patch test interpretations. Our aim is ...
Humans Neural Networks, Computer Female Dermoscopy Male Prospective Studies Retrospective Studies Patch Tests
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Dermatologist versus artificial intelligence confidence in dermoscopy diagnosis: Complementary information that may affect decision-making.

Experimental dermatology Aug 3, 2023
In dermatology, deep learning may be applied for skin lesion classification. However, for a given input image, a neural network only outputs a label, obtained using the class probabilities, which do not model uncertainty. Our group developed a novel ...
Skin Diseases Dermoscopy Dermatologists Humans Melanoma Skin Neoplasms Artificial Intelligence
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Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.

Neural networks : the official journal of the International Neural Network Society Jan 24, 2023
BACKGROUND: The idea of smart healthcare has gradually gained attention as a result of the information technology industry's rapid development. Smart healthcare uses next-generation technologies i.e., artificial intelligence (AI) and Internet of Thin...
Skin Neoplasms Dermoscopy Deep Learning Algorithms Delivery of Health Care Humans Melanoma Artificial Intelligence
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Intraclass Clustering-Based CNN Approach for Detection of Malignant Melanoma.

Sensors (Basel, Switzerland) Jan 13, 2023
This paper describes the process of developing a classification model for the effective detection of malignant melanoma, an aggressive type of cancer in skin lesions. Primary focus is given on fine-tuning and improving a state-of-the-art convolutiona...
Melanoma, Cutaneous Malignant Dermoscopy Cluster Analysis Artificial Intelligence Melanoma Humans Neural Networks, Computer
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Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network.

Acta dermato-venereologica Oct 11, 2022
Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with...
Melanoma Skin Neoplasms Deep Learning Dermatologists Dermoscopy Prospective Studies Retrospective Studies Humans Neural Networks, Computer
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Dermoscopy and skin imaging light sources: a comparison and review of spectral power distribution and color consistency.

Journal of biomedical optics Aug 8, 2022
SIGNIFICANCE: Dermoscopes incorporate light, polarizers, and optical magnification into a handheld tool that is commonly used by dermatologists to evaluate skin findings. Diagnostic accuracy is improved when dermoscopes are used, and some major artif...
Image Processing, Computer-Assisted Diagnostic Imaging Skin Artificial Intelligence Dermoscopy
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A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity.

PloS one Aug 4, 2022
The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class resemblance between malignant and benign lesions, and the presence of various artifacts including hairs make automated melanoma recognition in dermos...
Dermoscopy Deep Learning Artifacts Melanoma Skin Neoplasms Humans Neural Networks, Computer
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