Dermatology

Automated grading of acne vulgaris by deep learning with convolutional neural networks.

BACKGROUND: The visual assessment and severity grading of acne vulgaris by physicians can be subject...

Progressive Transfer Learning and Adversarial Domain Adaptation for Cross-Domain Skin Disease Classification.

Deep learning has been used to analyze and diagnose various skin diseases through medical imaging. H...

GoogLeNet-Based Ensemble FCNet Classifier for Focal Liver Lesion Diagnosis.

Transfer learning techniques are recently preferred for the computer aided diagnosis (CAD) of variet...

A superpixel-driven deep learning approach for the analysis of dermatological wounds.

BACKGROUND: The image-based identification of distinct tissues within dermatological wounds enhances...

Technical considerations of multi-parametric tissue outcome prediction methods in acute ischemic stroke patients.

Decisions regarding acute stroke treatment rely heavily on imaging, but interpretation can be diffic...

Superior skin cancer classification by the combination of human and artificial intelligence.

BACKGROUND: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in d...

Development and accuracy of an artificial intelligence algorithm for acne grading from smartphone photographs.

We developed an artificial intelligence algorithm (AIA) for smartphones to determine the severity of...

Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation.

Deep learning networks have recently been shown to outperform other segmentation methods on various ...

Detection and Monitoring of Thermal Lesions Induced by Microwave Ablation Using Ultrasound Imaging and Convolutional Neural Networks.

Microwave ablation (MWA) for cancer treatment is frequently monitored by ultrasound (US) B-mode imag...

Gabor wavelet-based deep learning for skin lesion classification.

Skin cancer cases are increasing and becoming one of the main problems worldwide. Skin cancer is kno...

Deep Learning to Improve Breast Cancer Detection on Screening Mammography.

The rapid development of deep learning, a family of machine learning techniques, has spurred much in...

Identifying Phenotypes of Atopic Dermatitis in a Longitudinal United States Cohort Using Unbiased Statistical Clustering.

Examining plant uptake and translocation of emerging contaminants using machine learning: Implications to food security.

When water and solutes enter the plant root through the epidermis, organic contaminants in solution ...

Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.

BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologist...

Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.

Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose ...

Deep neural networks are superior to dermatologists in melanoma image classification.

BACKGROUND: Melanoma is the most dangerous type of skin cancer but is curable if detected early. Rec...

Cross-registry neural domain adaptation to extract mutational test results from pathology reports.

OBJECTIVE: We study the performance of machine learning (ML) methods, including neural networks (NNs...

Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding.

White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their charac...

Support Vector Machine Classification of Nonmelanoma Skin Lesions Based on Fluorescence Lifetime Imaging Microscopy.

Early diagnosis of malignant skin lesions is critical for prompt treatment and a clinical prognosis ...

Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study.

BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preter...

Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging.

BACKGROUND AND PURPOSE: Most brain lesions are characterized by hyperintense signal on FLAIR. We sou...