Dermatology

Latest AI and machine learning research in dermatology for healthcare professionals.

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Subcategories: Atopy Psoriasis
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Spectrum-based deep learning framework for dermatological pigment analysis and simulation.

BACKGROUND: Deep learning in dermatology presents promising tools for automated diagnosis but faces ...

Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects.

In recent years, there has been a significant improvement in the accuracy of the classification of p...

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate ...

Utilization of machine learning for dengue case screening.

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide,...

Contrastive Learning vs. Self-Learning vs. Deformable Data Augmentation in Semantic Segmentation of Medical Images.

To develop a robust segmentation model, encoding the underlying features/structures of the input dat...

HTC-retina: A hybrid retinal diseases classification model using transformer-Convolutional Neural Network from optical coherence tomography images.

Retinal diseases are among nowadays major public health issues, deservedly needing advanced computer...

Preservative contact allergy in occupational dermatitis: a machine learning analysis.

Occupational dermatoses impose a significant socioeconomic burden. Allergic contact dermatitis relat...

Automatic evaluation of Nail Psoriasis Severity Index using deep learning algorithm.

Nail psoriasis is a chronic condition characterized by nail dystrophy affecting the nail matrix and ...

Deep learning-based prediction of compressive strength of eco-friendly geopolymer concrete.

The greenhouse gases cause global warming on Earth. The cement production industry is one of the lar...

Enhancing Skin Cancer Diagnosis Using Swin Transformer with Hybrid Shifted Window-Based Multi-head Self-attention and SwiGLU-Based MLP.

Skin cancer is one of the most frequently occurring cancers worldwide, and early detection is crucia...

Optimized attention-induced multihead convolutional neural network with efficientnetv2-fostered melanoma classification using dermoscopic images.

Melanoma is an uncommon and dangerous type of skin cancer. Dermoscopic imaging aids skilled dermatol...

TumFlow: An AI Model for Predicting New Anticancer Molecules.

Melanoma is the fifth most common cancer in the United States. Conventional drug discovery methods a...

Diagnosing contact dermatitis using machine learning: A review.

BACKGROUND: Machine learning (ML) offers an opportunity in contact dermatitis (CD) research, where w...

Automatized self-supervised learning for skin lesion screening.

Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide...

Hybrid CNN-Transformer Network With Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-Contrast CT Scans.

Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS). Non-cont...

MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3-D CT Lesions.

With the renaissance of deep learning, automatic diagnostic algorithms for computed tomography (CT) ...

GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status.

Noninvasively and accurately predicting the epidermal growth factor receptor (EGFR) mutation status ...

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