Dermatology

Characterization of Antiphospholipid Syndrome Atherothrombotic Risk by Unsupervised Integrated Transcriptomic Analyses.

OBJECTIVE: Our aim was to characterize distinctive clinical antiphospholipid syndrome phenotypes and...

Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers.

Whole-slide histology images contain information that is valuable for clinical and basic science inv...

Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification.

To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT...

Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis.

Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagno...

Artificial intelligence in the diagnosis of pediatric allergic diseases.

Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines ca...

The design and application of an automated microscope developed based on deep learning for fungal detection in dermatology.

BACKGROUND: Light microscopy to study the infection of fungi in skin specimens is time-consuming and...

How to Extract More Information With Less Burden: Fundus Image Classification and Retinal Disease Localization With Ophthalmologist Intervention.

Image classification using convolutional neural networks (CNNs) outperforms other state-of-the-art m...

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

BACKGROUND: Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwid...

Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.

IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epider...

A Prospective Randomised Study to Assess the Analgesic Efficacy of Serratus Anterior Plane (SAP) Block for Modified Radical Mastectomy Under General Anaesthesia.

OBJECTIVE: Breast cancer is the most common malignancy among women and often requires surgery for th...

Dermal epidermal junction detection for full-field optical coherence tomography data of human skin by deep learning.

Full-field optical coherence tomography (FF-OCT) has been developed to obtain three-dimensional (3D)...

Comparison of 11 automated PET segmentation methods in lymphoma.

Segmentation of lymphoma lesions in FDG PET/CT images is critical in both assessing individual lesio...

A Deep Learning Approach to Photoacoustic Wavefront Localization in Deep-Tissue Medium.

Optical photons undergo strong scattering when propagating beyond 1-mm deep inside biological tissue...

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer.

We apply for the first-time interpretable deep learning methods simultaneously to the most common sk...

The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis.

The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D mode...

A nanoemulsion-based nanogel of essential oil with leishmanicidal activity against and .

Cutaneous leishmaniasis is one of the diseases that severely affects human skin. Nanogels are the we...

Comparison of Prostate MRI Lesion Segmentation Agreement Between Multiple Radiologists and a Fully Automatic Deep Learning System.

PURPOSE:  A recently developed deep learning model (U-Net) approximated the clinical performance of ...

Development of a light-weight deep learning model for cloud applications and remote diagnosis of skin cancers.

Skin cancer is among the 10 most common cancers. Recent research revealed the superiority of artific...

Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are...

Use of an Artificial Neural Network to Identify Patient Clusters in a Large Cohort of Patients with Melanoma by Simultaneous Analysis of Costs and Clinical Characteristics.

Separability of Acute Cerebral Infarction Lesions in CT Based Radiomics: Toward Artificial Intelligence-Assisted Diagnosis.

This study aims at analyzing the separability of acute cerebral infarction lesions which were invisi...