Oncology/Hematology

Skin Cancer

Latest AI and machine learning research in skin cancer for healthcare professionals.

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A Novel System for Functional Determination of Variants of Uncertain Significance using Deep Convolutional Neural Networks.

Many drugs are developed for commonly occurring, well studied cancer drivers such as vemurafenib for...

Artificial intelligence as the next step towards precision pathology.

Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of c...

An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis.

Automatic skin lesion analysis of dermoscopy images remains a challenging topic. In this paper, we p...

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...

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...

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...

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