AIMC Topic: Skin

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Optimization of percutaneous intervention robotic system for skin insertion force.

International journal of computer assisted radiology and surgery
PURPOSE: Percutaneous puncture is a common interventional procedure, and its effectiveness is influenced by the insertion force of the needle. To optimize outcomes, we focus on reducing the peak force of the needle in the skin, aiming to apply this m...

Automated acute skin toxicity scoring in a mouse model through deep learning.

Radiation and environmental biophysics
This study presents a novel approach to skin toxicity assessment in preclinical radiotherapy trials through an advanced imaging setup and deep learning. Skin reactions, commonly associated with undesirable side effects in radiotherapy, were meticulou...

CAD-PsorNet: deep transfer learning for computer-assisted diagnosis of skin psoriasis.

Scientific reports
Psoriasis, being a chronic, inflammatory, lifelong skin disorder, has become a major threat to the human population. The precise and effective diagnosis of psoriasis continues to be difficult for clinicians due to its varied nature. In northern India...

Identification and validation of interferon-stimulated gene 15 as a biomarker for dermatomyositis by integrated bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: Dermatomyositis (DM) is an autoimmune disease that primarily affects the skin and muscles. It can lead to increased mortality, particularly when patients develop associated malignancies or experience fatal complications such as pulmonary ...

Machine learning accelerates the discovery of epitope-based dual-bioactive peptides against skin infections.

International journal of antimicrobial agents
OBJECTIVES: Skin injuries and infections are an inevitable part of daily human life, particularly with chronic wounds, becoming an increasing socioeconomic burden. In treating skin infections and promoting wound healing, bioactive peptides may hold s...

A Multi-level ensemble approach for skin lesion classification using Customized Transfer Learning with Triple Attention.

PloS one
Skin lesions encompass a variety of skin abnormalities, including skin diseases that affect structure and function, and skin cancer, which can be fatal and arise from abnormal cell growth. Early detection of lesions and automated prediction is crucia...

Integrating color histogram analysis and convolutional neural networks for skin lesion classification.

Computers in biology and medicine
The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue-gray. This study introduces a nov...

Training artificial neural networks using self-organizing migrating algorithm for skin segmentation.

Scientific reports
This study presents an application of the self-organizing migrating algorithm (SOMA) to train artificial neural networks for skin segmentation tasks. We compare the performance of SOMA with popular gradient-based optimization methods such as ADAM and...

Squid-Inspired Anti-Salt Skin-Like Elastomers With Superhigh Damage Resistance for Aquatic Soft Robots.

Advanced materials (Deerfield Beach, Fla.)
Cephalopod skins evolve multiple functions in response to environmental adaptation, encompassing nonlinear mechanoreponse, damage tolerance property, and resistance to seawater. Despite tremendous progress in skin-mimicking materials, the integration...

Image-Based Artificial Intelligence in Psoriasis Assessment: The Beginning of a New Diagnostic Era?

American journal of clinical dermatology
Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and healthcare systems, creating an urgent need for optimized diagnosis, treatment, and management. In ...