Dermatology

A Visually Interpretable Deep Learning Framework for Histopathological Image-Based Skin Cancer Diagnosis.

Owing to the high incidence rate and the severe impact of skin cancer, the precise diagnosis of mali...

Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images.

Stroke is an acute cerebral vascular disease that is likely to cause long-term disabilities and deat...

A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning.

Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures an...

Dark corner artefact and diagnostic performance of a market-approved neural network for skin cancer classification.

BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNN) have proven dermatologist-level perfo...

Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies.

To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients ...

Predicting Infarct Core From Computed Tomography Perfusion in Acute Ischemia With Machine Learning: Lessons From the ISLES Challenge.

BACKGROUND AND PURPOSE: The ISLES challenge (Ischemic Stroke Lesion Segmentation) enables globally d...

Comparison of image quality and lesion diagnosis in abdominopelvic unenhanced CT between reduced-dose CT using deep learning post-processing and standard-dose CT using iterative reconstruction: A prospective study.

PURPOSE: To compare image quality and lesion diagnosis between reduced-dose abdominopelvic unenhance...

Response to "Reply to 'A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance: Simplifying the diagnosis of complicated diseases.' Has the complicated disease been simplified too much?" Artificial intelligence system is helpful for diagnosis of cutaneous lupus erythematosus.

Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels.

AIM: To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic co...

Reply to "A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance - simplifying the diagnosis of complicated diseases": Machine learning evaluations need to consider the true clinical context.

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because...

Interpretation of allele-specific chromatin accessibility using cell state-aware deep learning.

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellu...

Predicting the clinical management of skin lesions using deep learning.

Automated machine learning approaches to skin lesion diagnosis from images are approaching dermatolo...

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data.

Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathoph...

Adopting low-shot deep learning for the detection of conjunctival melanoma using ocular surface images.

BACKGROUND AND OBJECTIVE: The purpose of the present study was to investigate low-shot deep learning...

Ultra-high-frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions.

Malignant melanoma (MM) is one of the most dangerous skin cancers. The aim of this study was to pres...

Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking.

Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop...

Deep learning approach to skin layers segmentation in inflammatory dermatoses.

Monitoring skin layers with medical imaging is critical to diagnosing and treating patients with chr...

Automated severity scoring of atopic dermatitis patients by a deep neural network.

Scoring atopic dermatitis (AD) severity with the Eczema Area and Severity Index (EASI) in an objecti...

Meniscal lesion detection and characterization in adult knee MRI: A deep learning model approach with external validation.

PURPOSE: Evaluation of a deep learning approach for the detection of meniscal tears and their charac...

Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model.

Background Missing MRI sequences represent an obstacle in the development and use of deep learning (...