AIMC Topic: Skin

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Data augmentation in dermatology image recognition using machine learning.

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: Each year in the United States, over 80 million people are affected by acne, atopic dermatitis, rosacea, psoriasis, and impetigo. Artificial intelligence and machine learning could prove to be a good tool for assisting in the diagnosis of...

Digital hair segmentation using hybrid convolutional and recurrent neural networks architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Skin melanoma is one of the major health problems in many countries. Dermatologists usually diagnose melanoma by visual inspection of moles. Digital hair removal can provide a non-invasive way to remove hair and hair-like re...

Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper addresses two key problems of skin lesion classification. The first problem is the effective use of high-resolution images with pretrained standard architectures for image classification. The second problem is the high-class imb...

A comparative study of deep learning architectures on melanoma detection.

Tissue & cell
Melanoma is the most aggressive type of skin cancer, which significantly reduces the life expectancy. Early detection of melanoma can reduce the morbidity and mortality associated with skin cancer. Dermoscopic images acquired by dermoscopic instrumen...

Novel taxonomy-independent deep learning microbiome approach allows for accurate classification of different forensically relevant human epithelial materials.

Forensic science international. Genetics
Correct identification of different human epithelial materials such as from skin, saliva and vaginal origin is relevant in forensic casework as it provides crucial information for crime reconstruction. However, the overlap in human cell type composit...

Bioinspired Hairy Skin Electronics for Detecting the Direction and Incident Angle of Airflow.

ACS applied materials & interfaces
The human skin has inspired multimodal detection using smart devices or systems in fields including biomedical engineering, robotics, and artificial intelligence. Hairs of a high aspect ratio (AR) connected to follicles, in particular, detect subtle ...

Transfer learning for predicting human skin sensitizers.

Archives of toxicology
Computational prioritization of chemicals for potential skin sensitization risks plays essential roles in the risk assessment of environmental chemicals and drug development. Given the huge number of chemicals for testing, computational methods enabl...

Contact Modelling and Tactile Data Processing for Robot Skins.

Sensors (Basel, Switzerland)
Tactile sensing is a key enabling technology to develop complex behaviours for robots interacting with humans or the environment. This paper discusses computational aspects playing a significant role when extracting information about contact events. ...

Prediction of skin dose in low-kV intraoperative radiotherapy using machine learning models trained on results of in vivo dosimetry.

Medical physics
PURPOSE: The purpose of this study was to implement a machine learning model to predict skin dose from targeted intraoperative (TARGIT) treatment resulting in timely adoption of strategies to limit excessive skin dose.

Attention Residual Learning for Skin Lesion Classification.

IEEE transactions on medical imaging
Automated skin lesion classification in dermoscopy images is an essential way to improve the diagnostic performance and reduce melanoma deaths. Although deep convolutional neural networks (DCNNs) have made dramatic breakthroughs in many image classif...