AIMC Topic: Skin

Clear Filters Showing 41 to 50 of 382 articles

Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds.

PeerJ
BACKGROUND: To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-culture system that combines HaCaT keratinocytes (transfected with a luciferase plasmid driven by the AKR1C2 promoter) and THP-1 cells for machine lear...

Dual scale light weight cross attention transformer for skin lesion classification.

PloS one
Skin cancer is rapidly growing globally. In the past decade, an automated diagnosis system has been developed using image processing and machine learning. The machine learning methods require hand-crafted features, which may affect performance. Recen...

Transfer Contrastive Learning for Raman Spectroscopy Skin Cancer Tissue Classification.

IEEE journal of biomedical and health informatics
Using Raman spectroscopy (RS) signals for skin cancer tissue classification has recently drawn significant attention, because of its non-invasive optical technique, which uses molecular structures and conformations within biological tissue for diagno...

AFCF-Net: A novel U-Net based asymmetric feature calibration and fusion network for skin lesion image segmentation.

PloS one
Skin lesion segmentation plays a pivotal role in the diagnosis and treatment of skin diseases. By using deep neural networks to segment lesion areas, doctors can more accurately assess the severity of health-related conditions of patients and promptl...

Skin Phototype Classification with Machine Learning Based on Broadband Optical Measurements.

Sensors (Basel, Switzerland)
The Fitzpatrick Skin Phototype Classification (FSPC) scale is widely used to categorize skin types but has limitations such as the underrepresentation of darker skin phototypes, low classification resolution, and subjectivity. These limitations may c...

Mormyroidea-inspired electronic skin for active non-contact three-dimensional tracking and sensing.

Nature communications
The capacity to discern and locate positions in three-dimensional space is crucial for human-machine interfaces and robotic perception. However, current soft electronics can only obtain two-dimensional spatial locations through physical contact. In t...

Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images.

Sensors (Basel, Switzerland)
Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the ...

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...