Dermatology

Systematic review of machine learning for diagnosis and prognosis in dermatology.

Software systems using artificial intelligence for medical purposes have been developed in recent y...

Fixation of intracapsular fracture of the femoral neck using combined peripheral nerve blocks and transthoracic echocardiography in a patient with severe obstructive hypertrophic cardiomyopathy: a case report.

BACKGROUND: Hypertrophic obstructive cardiomyopathy (HOCM) is a type of hypertrophic cardiomyopathy ...

Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

PURPOSE: Biomarkers for disease-specific survival (DSS) in early-stage melanoma are needed to select...

Smart identification of psoriasis by images using convolutional neural networks: a case study in China.

BACKGROUND: Psoriasis is a chronic inflammatory skin disease, which holds a high incidence in China....

Antioxidant, Anti-Melanogenic and Anti-Wrinkle Effects of .

In this study, the antioxidant, anti-xanthine oxidase, anti-melanogenic and anti-wrinkle effects of ...

Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks.

The use of Computed Tomography (CT) imaging for patients with stroke symptoms is an essential step f...

Dense pooling layers in fully convolutional network for skin lesion segmentation.

One of the essential tasks in medical image analysis is segmentation and accurate detection of borde...

A network underlying human higher-order motor control: Insights from machine learning-based lesion-behaviour mapping in apraxia of pantomime.

Neurological patients with apraxia of pantomime provide us with a unique opportunity to study the ne...

Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions.

IMPORTANCE: A high proportion of suspicious pigmented skin lesions referred for investigation are be...

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...

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 ...

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...

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...