Skin Cancer

Reply to the letter to the editor: 'Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images'.

Artificial intelligence and melanoma detection: friend or foe of dermatologists?

The significance of early diagnosis for melanoma prognosis and survival cannot be understated. The p...

Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas.

BACKGROUND: Deep learning convolutional neural networks (CNN) may assist physicians in the diagnosis...

Melanoma recognition by a deep learning convolutional neural network-Performance in different melanoma subtypes and localisations.

BACKGROUND: Deep learning convolutional neural networks (CNNs) show great potential for melanoma dia...

Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.

PURPOSE: Tumor genomic features have been of particular interest because of their potential impact o...

Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common form of primary adult liver cancer. After nearly a...

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex...

A Machine-Learning Approach to Identify a Prognostic Cytokine Signature That Is Associated With Nivolumab Clearance in Patients With Advanced Melanoma.

Lower clearance of immune checkpoint inhibitors is a predictor of improved overall survival (OS) in ...

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks.

The importance of T cells in immunotherapy has motivated developing technologies to improve therapeu...

Efficient expression of EpEX in the cytoplasm of using thioredoxin fusion protein.

Recombinant epithelial cell adhesion molecule extracellular domain (EpEX) has a high potential as a ...

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the...

Skin cancer diagnosis based on optimized convolutional neural network.

Early detection of skin cancer is very important and can prevent some skin cancers, such as focal ce...

Poly(ethylene glycol)-poly(ε-caprolactone)-based micelles for solubilization and tumor-targeted delivery of silibinin.

Silibinin is a naturally occurring compound with known positive impacts on prevention and treatment...

DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity.

Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen predic...

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...

Re: Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images.

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...

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

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

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal.

Differential gene expression analysis is an important technique for understanding disease states. Th...

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...