AIMC Topic: Skin Neoplasms
Clear Filters Showing 401 to 410 of 514 articles
Dermatologist-level classification of skin cancer with deep neural networks.
Nature
Jan 25, 2017
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of ski...
Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model.
IEEE transactions on medical imaging
Dec 1, 2016
We develop a novel method for classifying melanocytic tumors as benign or malignant by the analysis of digital dermoscopy images. The algorithm follows three steps: first, lesions are extracted using a self-generating neural network (SGNN); second, f...
Computer-Aided Diagnosis of Micro-Malignant Melanoma Lesions Applying Support Vector Machines.
BioMed research international
Jun 13, 2016
Background. One of the fatal disorders causing death is malignant melanoma, the deadliest form of skin cancer. The aim of the modern dermatology is the early detection of skin cancer, which usually results in reducing the mortality rate and less exte...
Adaptable texture-based segmentation by variance and intensity for automatic detection of semitranslucent and pink blush areas in basal cell carcinoma.
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)
Mar 16, 2016
BACKGROUND: Pink blush is a common feature in basal cell carcinoma (BCC). A related feature, semitranslucency, appears as smooth pink or orange regions resembling skin color. We introduce an automatic method for detection of these features based on s...
An unsupervised feature learning framework for basal cell carcinoma image analysis.
Artificial intelligence in medicine
Apr 23, 2015
OBJECTIVE: The paper addresses the problem of automatic detection of basal cell carcinoma (BCC) in histopathology images. In particular, it proposes a framework to both, learn the image representation in an unsupervised way and visualize discriminati...
Staining and Labeling
Unsupervised Machine Learning
Predictive Value of Tests
Biopsy
Image Interpretation, Computer-Assisted
Area Under Curve
Discriminant Analysis
Reproducibility of Results
ROC Curve
Decision Support Systems, Clinical
Automation, Laboratory
Humans
Skin Neoplasms
Pathology, Clinical
Decision Support Techniques
Carcinoma, Basal Cell
Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.
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)
Mar 22, 2015
BACKGROUND/PURPOSE: Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature ...
Four-class classification of skin lesions with task decomposition strategy.
IEEE transactions on bio-medical engineering
Aug 15, 2014
This paper proposes a new computer-aided method for the skin lesion classification applicable to both melanocytic skin lesions (MSLs) and nonmelanocytic skin lesions (NoMSLs). The computer-aided skin lesion classification has drawn attention as an ai...
Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.
International journal of dermatology
Sep 1, 2025
This comprehensive review examines artificial intelligence (AI) applications in dermatology, approved by the United States (U.S.) Food and Drug Administration (FDA) and international organizations, evaluating their clinical implementation and impact ...
The Development and Evaluation of a Convolutional Neural Network for Cutaneous Melanoma Detection in Whole Slide Images.
Archives of pathology & laboratory medicine
Sep 1, 2025
CONTEXT.—: The current melanoma staging system does not account for 26% of the variance seen in melanoma-specific survival, therefore our ability to predict patient outcome is not fully elucidated. Morphology may be of greater significance than in ot...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32510
- Neural Networks, Computer 30481
- Algorithms 27731
- Deep Learning 27277
- Artificial Intelligence 25203
- Robotics 13428
- Image Processing, Computer-Assisted 9883
- Retrospective Studies 9527
- Magnetic Resonance Imaging 6481
- Reproducibility of Results 5744
- Tomography, X-Ray Computed 4956
- Support Vector Machine 4812
- Computational Biology 4392
- Brain 4186
- Computer Simulation 3962
Recent Journals
- Scientific reports 7009
- Sensors (Basel, Switzerland) 4794
- PloS one 4295
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2037
- Computational intelligence and neuroscience 1931
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1395
- IEEE journal of biomedical and health informatics 1191
- Journal of chemical information and modeling 1083
- Nature communications 1070
- Computer methods and programs in biomedicine 895
- Bioinformatics (Oxford, England) 879
- Journal of medical Internet research 878
- IEEE transactions on neural networks and learning systems 859