Dermatology

Artificial intelligence for breast ultrasound: An adjunct tool to reduce excessive lesion biopsy.

PURPOSE: To determine whether adding an artificial intelligence (AI) system to breast ultrasound (US...

Accurate surface ultraviolet radiation forecasting for clinical applications with deep neural network.

Exposure to appropriate doses of UV radiation provides enormously health and medical treatment benef...

Comparison of performance of a deep learning-based mobile application with non-dermatologist physicians in the diagnosis of common skin diseases.

Personalized prediction of early childhood asthma persistence: A machine learning approach.

Early childhood asthma diagnosis is common; however, many children diagnosed before age 5 experience...

A convolutional neural network architecture for the recognition of cutaneous manifestations of COVID-19.

During the COVID-19 pandemic, dermatologists reported an array of different cutaneous manifestations...

Diagnostic Performance of Deep Learning-Based Lesion Detection Algorithm in CT for Detecting Hepatic Metastasis from Colorectal Cancer.

OBJECTIVE: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) i...

Pushing the boundaries of computer-aided diagnosis of melanoma.

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gi...

Evaluation of the Use of Single- and Multi-Magnification Convolutional Neural Networks for the Determination and Quantitation of Lesions in Nonclinical Pathology Studies.

Digital pathology platforms with integrated artificial intelligence have the potential to increase t...

Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.

OBJECTIVES: To evaluate image quality and lesion detection capabilities of low-dose (LD) portal veno...

A hierarchical three-step superpixels and deep learning framework for skin lesion classification.

Skin cancer is one of the most common and dangerous cancer that exists worldwide. Malignant melanoma...

A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance: Simplifying the diagnosis of complicated diseases.

Deep learning-based grading of ductal carcinoma in situ in breast histopathology images.

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive duct...

Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study.

PURPOSE: Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine...

Accuracy of Algorithms to Identify People with Atopic Dermatitis in Ontario Routinely Collected Health Databases.

Accelerated white matter lesion analysis based on simultaneous and quantification using magnetic resonance fingerprinting and deep learning.

PURPOSE: To develop an accelerated postprocessing pipeline for reproducible and efficient assessment...

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract.

Accurate lesion segmentation based on endoscopy images is a fundamental task for the automated diagn...

Global guidance network for breast lesion segmentation in ultrasound images.

Automatic breast lesion segmentation in ultrasound helps to diagnose breast cancer, which is one of ...

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model.

BACKGROUND AND PURPOSE: Malignant melanoma is an aggressive skin cancer in which brain metastases ar...

An anatomical knowledge-based MRI deep learning pipeline for white matter hyperintensity quantification associated with cognitive impairment.

Recent studies have confirmed that white matter hyperintensities (WMHs) accumulated in strategic bra...

CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation.

Accurate medical image segmentation is essential for diagnosis and treatment planning of diseases. C...