Dermatology

Explainable artificial intelligence in skin cancer recognition: A systematic review.

BACKGROUND: Due to their ability to solve complex problems, deep neural networks (DNNs) are becoming...

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and ...

A novel approach for skin lesion symmetry classification with a deep learning model.

Skin cancer has become a public health problem due to its increasing incidence. However, the maligna...

Artificial intelligence recognition of cutaneous chronic graft-versus-host disease by a deep learning neural network.

Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population.

(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, spec...

Fully Convolutional Neural Network Deep Learning Model Fully in Patients with Type 2 Diabetes Complicated with Peripheral Neuropathy by High-Frequency Ultrasound Image.

This study was aimed at exploring the diagnostic value of high-frequency ultrasound imaging based on...

Deep Learning-Based Classification for Melanoma Detection Using XceptionNet.

Skin cancer is one of the most common types of cancer in the world, accounting for at least 40% of a...

Autonomous diagnosis of pediatric cutaneous vascular anomalies using a convolutional neural network.

OBJECTIVES: Design and validate a novel handheld device for the autonomous diagnosis of pediatric va...

Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19.

Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epica...

Caffeoyl malic acid is a potential dual inhibitor targeting TNFα/IL-4 evaluated by a combination strategy of network analysis-deep learning-molecular simulation.

Atopic dermatitis (AD) is a common inflammatory skin disease involving multiple signaling pathways. ...

Deep Learning-Based Automatic Assessment of Radiation Dermatitis in Patients With Nasopharyngeal Carcinoma.

PURPOSE: Radiation dermatitis (RD) is a common, unpleasant side effect of patients receiving radiati...

Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.

In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and si...

Modeling solubility of CO-N gas mixtures in aqueous electrolyte systems using artificial intelligence techniques and equations of state.

Determining the solubility of non-hydrocarbon gases such as carbon dioxide (CO) and nitrogen (N) in ...

A Cloud Approach for Melanoma Detection Based on Deep Learning Networks.

In the era of digitized images, the goal is to extract information from them and create new knowledg...

Uncertainty-aware skin cancer detection: The element of doubt.

Artificial intelligence (AI)-based medical diagnosis has received huge attention due to its potentia...

An Efficient Stacked Deep Transfer Learning Model for Automated Diagnosis of Lyme Disease.

Lyme disease is one of the most common vector-borne infections. It typically causes cardiac illnesse...

TATL: Task agnostic transfer learning for skin attributes detection.

Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network an...

Measurement of Body Surface Area for Psoriasis Using U-net Models.

During the evaluation of body surface area (BSA), precise measurement of psoriasis is crucial for as...

Artificial intelligence and deep learning to map immune cell types in inflamed human tissue.

Biopsies of inflammatory tissue contain a complex network of interacting cells, orchestrating the im...

Artificial intelligence and melanoma: A comprehensive review of clinical, dermoscopic, and histologic applications.

Melanoma detection, prognosis, and treatment represent challenging and complex areas of cutaneous on...

Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases.

PURPOSE: Non-small cell lung cancer (NSCLC) tends to metastasize to the brain. Between 10 and 60% of...