Oncology/Hematology

Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients.

PURPOSE: Identification and delineation of the gross tumour and malignant nodal volume (GTV) in medi...

Systematic characterization of mutations altering protein degradation in human cancers.

The ubiquitin-proteasome system (UPS) is the primary route for selective protein degradation in huma...

Automated diagnostic support system with deep learning algorithms for distinction of Philadelphia chromosome-negative myeloproliferative neoplasms using peripheral blood specimen.

Philadelphia chromosome-negative myeloproliferative neoplasms (Ph-negative MPNs) such as polycythemi...

Forecasting influenza activity using machine-learned mobility map.

Human mobility is a primary driver of infectious disease spread. However, existing data is limited i...

Deep learning-augmented radiotherapy visualization with a cylindrical radioluminescence system.

This study aims to demonstrate a low-cost camera-based radioluminescence imaging system (CRIS) for h...

Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.

OBJECTIVES: To evaluate a deep learning-based model using model-generated segmentation masks to diff...

Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative reconstruction.

OBJECTIVE: To evaluate the effect of a commercial deep learning algorithm on the image quality of ch...

Deep Learning With 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

BACKGROUND: Microvascular invasion (MVI) is a critical prognostic factor of hepatocellular carcinoma...

Editorial on "Deep Learning with 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma".

A deep-learning semantic segmentation approach to fully automated MRI-based left-ventricular deformation analysis in cardiotoxicity.

Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DEN...

TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties.

Immunotherapy is a research area with great potential in drug discovery for cancer treatment. Becaus...

A novel gene selection method for gene expression data for the task of cancer type classification.

Cancer is a poligenetic disease with each cancer type having a different mutation profile. Genomic d...

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System.

At present, human health is threatened by many diseases, and lung cancer is one of the most dangerou...

BloodCaps: A capsule network based model for the multiclassification of human peripheral blood cells.

BACKGROUND AND OBJECTIVE: The classification of human peripheral blood cells yields significance in ...

Use of Artificial Intelligence in the Prediction of Malignant Potential of Gastric Gastrointestinal Stromal Tumors.

BACKGROUND AND AIMS: This study aimed to investigate whether AI via a deep learning algorithm using ...

Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer.

PURPOSE: Accurate lymph node (LN) malignancy classification is essential for treatment target identi...

Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?

PURPOSE: Convolutional neural networks (CNNs) show potential for delineating cancers on contrast-enh...

Optimizing ANFIS using simulated annealing algorithm for classification of microarray gene expression cancer data.

In the medical field, successful classification of microarray gene expression data is of major impor...

Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model's Complexity on Its Processing Speed.

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almos...

Investigating the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning model.

BACKGROUND: Survival analysis is an important part of cancer studies. In addition to the existing Co...

Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019.

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient car...