AIMC Topic: Skin

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Burn wound classification model using spatial frequency-domain imaging and machine learning.

Journal of biomedical optics
Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have...

Computational neural network in melanocytic lesions diagnosis: artificial intelligence to improve diagnosis in dermatology?

European journal of dermatology : EJD
Diagnosis in dermatology is largely based on contextual factors going far beyond the visual and dermoscopic inspection of a lesion. Diagnostic tools such as the different types of dermoscopy, confocal microscopy and optical coherence tomography (OCT)...

A new deep learning model for assisted diagnosis on electrocardiogram.

Mathematical biosciences and engineering : MBE
In order to enhance the accuracy of computer aided electrocardiogram analysis, we propose a deep learning model called CBRNN to assist diagnosis on electrocardiogram for clinical medical service. It combines two sub networks which are convolutional n...

Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

JAMA dermatology
IMPORTANCE: Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose.

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

Annals of oncology : official journal of the European Society for Medical Oncology
BACKGROUND: Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking.

Mahalanobis Outier Removal for Improving the Non-Viable Detection on Human Injuries.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Machine learning techniques have been recently applied for discriminating between Viable and Non-Viable tissues in animal wounds, to help surgeons to identify areas that need to be excised in the process of burn debridement. However, the presence of ...

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

IEEE transactions on biomedical circuits and systems
Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim t...

A flexible dual-mode proximity sensor based on cooperative sensing for robot skin applications.

The Review of scientific instruments
A flexible dual-mode proximity sensor has been designed and implemented, which is capable of combining capacitive-resistive detection in this paper. The capacitive type proximity sensor detecting is defined as mode-C, and the resistive type proximity...

Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

Medical physics
PURPOSE: Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surfac...

Non-invasive optical imaging techniques for burn-injured tissue detection for debridement surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Burn debridement is a challenging technique that requires significant skill to identify regions requiring excision and appropriate excision depth. A machine learning tool is being developed in order to assist surgeons by providing a quantitative asse...