Dermatology

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 malignancy risk of the lesions can be reduced if diagnosed at an early stage. To do so, it is essential to identify particular characteristics such as the symmetry of lesions. In this work, we present a novel approach for skin lesion symmetry classification of dermoscopic images based on deep learning tech...

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, specificity, and accuracy of the quantusSKIN system, a...

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 a fully convolutional neural network (FCN) for pe...

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 all cancers. Melanoma is considered as the 19th mos...

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 vascular anomalies using a convolutional neural netw...

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 epicardial adipose tissue (EAT) from low-dose computed ...

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. One of the effective treatment strategies of AD is...

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 radiation therapy. In clinical practice, the severity of ...

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 size of the skin lesion makes the segmentation task ...

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 water and brine is one of the most controversial c...

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 knowledge thanks to Computer Vision techniques, Machine Le...

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

Artificial intelligence (AI)-based medical diagnosis has received huge attention due to its potential to improve and accelerate the decision-making pr...

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 illnesses, neurologic illnesses, musculoskeletal disorders...

Deep learning for fully automatic detection, segmentation, and Gleason grade estimation of prostate cancer in multiparametric magnetic resonance images.

Although the emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), an...

A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging.

Over the past few years, positron emission tomography/computed tomography (PET/CT) imaging for computer-aided diagnosis has received increasing attent...

TATL: Task agnostic transfer learning for skin attributes detection.

Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However...

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 assessing disease severity and modulating treatment ...

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 immune or autoimmune response. While standard histol...

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 oncology with considerable impact on patient outcome...