Oncology/Hematology

Skin Cancer

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

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Data-Driven Deep Supervision for Medical Image Segmentation.

Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-depen...

BepFAMN: A Method for Linear B-Cell Epitope Predictions Based on Fuzzy-ARTMAP Artificial Neural Network.

The public health system is extremely dependent on the use of vaccines to immunize the population fr...

Computer-aided detection and segmentation of malignant melanoma lesions on whole-body F-FDG PET/CT using an interpretable deep learning approach.

BACKGROUND AND OBJECTIVE: In oncology, 18-fluorodeoxyglucose (F-FDG) positron emission tomography (P...

A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology.

Epstein-Barr virus-associated gastric cancer (EBVaGC) shows a robust response to immune checkpoint i...

Vaccine Therapy in Non-Small Cell Lung Cancer.

Immunotherapy using immune checkpoint modulators has revolutionized the oncology field, emerging as ...

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging.

This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cel...

Non-Invasive Measurement Using Deep Learning Algorithm Based on Multi-Source Features Fusion to Predict PD-L1 Expression and Survival in NSCLC.

BACKGROUND: Programmed death-ligand 1 (PD-L1) assessment of lung cancer in immunohistochemical assay...

Deep learning based on hematoxylin-eosin staining outperforms immunohistochemistry in predicting molecular subtypes of gastric adenocarcinoma.

In gastric cancer (GC), there are four molecular subclasses that indicate whether patients respond t...

Cancer insights from magnetic resonance spectroscopy of cells and excised tumors.

Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer...

Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population.

(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, spec...

Deep Learning-Based Classification for Melanoma Detection Using XceptionNet.

Skin cancer is one of the most common types of cancer in the world, accounting for at least 40% of a...

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accura...

Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.

In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and si...

A Cloud Approach for Melanoma Detection Based on Deep Learning Networks.

In the era of digitized images, the goal is to extract information from them and create new knowledg...

Deep learning using bulk RNA-seq data expands cell landscape identification in tumor microenvironment.

The tumor microenvironment (TME) profoundly influences tumor progression and affects immunotherapy r...

Functions of RNF Family in the Tumor Microenvironment and Drugs Prediction in Grade II/III Gliomas.

Increasing evidence has demonstrated that RING finger (RNF) proteins played a vital role in cellular...

Specific IgE and IgG4 Profiles of House Dust Mite Components in Allergen-Specific Immunotherapy.

BACKGROUND: Allergen immunotherapy (AIT) can induce immune tolerance to allergens by activating mult...

Artificial intelligence and melanoma: A comprehensive review of clinical, dermoscopic, and histologic applications.

Melanoma detection, prognosis, and treatment represent challenging and complex areas of cutaneous on...

New Trends in Melanoma Detection Using Neural Networks: A Systematic Review.

Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease t...

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