AIMC Topic: Skin Neoplasms

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Skin cancer detection from dermoscopic images using deep learning and fuzzy k-means clustering.

Microscopy research and technique Aug 27, 2021
Melanoma skin cancer is the most life-threatening and fatal disease among the family of skin cancer diseases. Modern technological developments and research methodologies made it possible to detect and identify this kind of skin cancer more effective...
Melanoma Skin Neoplasms Dermoscopy Humans Algorithms Deep Learning Cluster Analysis
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Discriminative deep learning based benignity/malignancy diagnosis of dermatologic ultrasound skin lesions with pretrained artificial intelligence architecture.

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) Aug 22, 2021
BACKGROUND: Deep-learning algorithms (DLAs) have been used in artificial intelligence aided ultrasonography diagnosis of thyroid and breast lesions. However, its use has not been described in the case of dermatologic ultrasound lesions. Our purpose w...
Neural Networks, Computer Artificial Intelligence Skin Neoplasms Humans Ultrasonography Sensitivity and Specificity Deep Learning
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Legal and ethical considerations of artificial intelligence in skin cancer diagnosis.

The Australasian journal of dermatology Aug 18, 2021
Artificial intelligence (AI) technology is becoming increasingly accurate and prevalent for the diagnosis of skin cancers. Commercially available AI diagnostic software is entering markets across the world posing new legal and ethical challenges for ...
Software Skin Neoplasms Liability, Legal Diagnosis, Computer-Assisted Informed Consent Humans Australia Malpractice Artificial Intelligence Confidentiality
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A benchmark for neural network robustness in skin cancer classification.

European journal of cancer (Oxford, England : 1990) Aug 11, 2021
BACKGROUND: One prominent application for deep learning-based classifiers is skin cancer classification on dermoscopic images. However, classifier evaluation is often limited to holdout data which can mask common shortcomings such as susceptibility t...
Humans Neural Networks, Computer Skin Neoplasms Benchmarking
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Image quality issues in teledermatology: A comparative analysis of artificial intelligence solutions.

Journal of the American Academy of Dermatology Aug 10, 2021
Artificial Intelligence Skin Neoplasms Deep Learning Humans
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Classification of large-scale image database of various skin diseases using deep learning.

International journal of computer assisted radiology and surgery Jul 26, 2021
PURPOSE: The purpose of this study was to develop a deep learning-based computer-aided diagnosis system for skin disease classification using photographic images of patients. The targets are 59 skin diseases, including localized and diffuse diseases ...
Humans Skin Neoplasms Reproducibility of Results Deep Learning Skin Diseases Photography
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Skin Cancer Detection Using Kernel Fuzzy C-Means and Improved Neural Network Optimization Algorithm.

Computational intelligence and neuroscience Jul 17, 2021
Early diagnosis of malignant skin cancer from images is a significant part of the cancer treatment process. One of the principal purposes of this research is to propose a pipeline methodology for an optimum computer-aided diagnosis of skin cancers. T...
Algorithms Support Vector Machine Humans Skin Neoplasms Neural Networks, Computer Diagnosis, Computer-Assisted
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An Evolutionary Approach for the Enhancement of Dermatological Images and Their Classification Using Deep Learning Models.

Journal of healthcare engineering Jul 15, 2021
Dermatological problems are the most widely spread skin diseases amongst human beings. They can be infectious, chronic, and sometimes may also lead to serious health problems such as skin cancer. Generally, rural area clinics lack trained dermatologi...
Carcinoma, Basal Cell Humans Neural Networks, Computer Deep Learning Melanoma Skin Neoplasms
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Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

The Journal of investigative dermatology Jul 13, 2021
Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied ...
Aged, 80 and over Adult Male Middle Aged Deep Learning Humans Dermoscopy Artificial Intelligence Reproducibility of Results Female Aged Skin Neoplasms Microscopy, Confocal Models, Biological Carcinoma, Basal Cell Automation Biopsy Physical Examination
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Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks.

Dermatology (Basel, Switzerland) Jul 8, 2021
BACKGROUND: The number of naevi on a person is the strongest risk factor for melanoma; however, naevus counting is highly variable due to lack of consistent methodology and lack of inter-rater agreement. Machine learning has been shown to be a valuab...
Imaging, Three-Dimensional Early Detection of Cancer Photography Whole Body Imaging Nevus Humans Sensitivity and Specificity Neural Networks, Computer Male Female Melanoma Skin Neoplasms Reproducibility of Results Aged Adult Middle Aged
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