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Skin

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Intelligent Bi-Dimensional Skin Biopsies of Rheumatoid Arthritis Based on Raman Spectral Imaging and Machine Learning.

Analytical chemistry
Rheumatoid arthritis (RA) is one of the most common autoimmune diseases worldwide, characterized by its progressive and irreversible nature. Early diagnosis is crucial for delaying disease progression and optimizing treatment strategies. Existing dia...

Mpox-XDE: an ensemble model utilizing deep CNN and explainable AI for monkeypox detection and classification.

BMC infectious diseases
The daily surge in cases in many nations has made the growing number of human monkeypox (Mpox) cases an important global concern. Therefore, it is imperative to identify Mpox early to prevent its spread. The majority of studies on Mpox identification...

Artificial intelligence challenge of discriminating cutaneous arteritis and polyarteritis nodosa based on hematoxylin-and-eosin images of skin biopsy specimens.

Pathology, research and practice
Diseases that develop necrotizing vasculitis of cutaneous muscular arteries include cutaneous arteritis (CA) and polyarteritis nodosa (PAN). It is difficult to distinguish them based on skin biopsy findings alone. This study demonstrated that artific...

Deep-Learning-Based Analysis of Electronic Skin Sensing Data.

Sensors (Basel, Switzerland)
E-skin is an integrated electronic system that can mimic the perceptual ability of human skin. Traditional analysis methods struggle to handle complex e-skin data, which include time series and multiple patterns, especially when dealing with intricat...

Deep-learning-enabled spatial frequency domain imaging of the spatiotemporal dynamics of skin physiology.

Journal of biomedical optics
SIGNIFICANCE: Spatial frequency domain imaging (SFDI) is an emerging optical imaging modality for visualizing tissue absorption and scattering properties. This approach is promising for noninvasive wide field-of-view (FOV) monitoring of biophysiologi...

Neural network analysis as a novel skin outcome in a trial of belumosudil in patients with systemic sclerosis.

Arthritis research & therapy
BACKGROUND: The modified Rodnan skin score (mRSS), a measure of systemic sclerosis (SSc) skin thickness, is agnostic to inflammation and vasculopathy. Previously, we demonstrated the potential of neural network-based digital pathology applied to SSc ...

Advancements in artificial intelligence for atopic dermatitis: diagnosis, treatment, and patient management.

Annals of medicine
Atopic dermatitis (AD) is a common and complex skin disease that significantly affects the quality of life of patients. The latest advances in artificial intelligence (AI) technology have introduced new methods for diagnosing, treating, and managing ...

Interpretable deep learning method to predict wound healing progress based on collagen fibers in wound tissue.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The dynamic evolution of collagen fibers during wound healing is crucial for assessing repair progression, guiding clinical treatment, and drug screening. Current quantitative methods analyzing collagen spatial patterns (den...

Using explainable machine learning to predict the irritation and corrosivity of chemicals on eyes and skin.

Toxicology letters
Contact with specific chemicals often results in corrosive and irritative responses in the eyes and skin, playing a pivotal role in assessing the potential hazards of personal care products, cosmetics, and industrial chemicals to human health. While ...

Artificial Intelligence Predicts Fitzpatrick Skin Type, Pigmentation, Redness, and Wrinkle Severity From Color Photographs of the Face.

Journal of cosmetic dermatology
BACKGROUND: Due to high patient demand, increasing numbers of non-dermatologists are performing skin assessments and carrying out laser interventions in medical spas, leading to inferior outcomes and higher complications. A machine learning tool that...