Oncology/Hematology

Breast Cancer

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

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Showing 295-315 of 6,446 articles
Assessing multiple MRI sequences in deep learning-based synthetic CT generation for MR-only radiation therapy of head and neck cancers.

PURPOSE: This study investigated the effect of multiple magnetic resonance (MR) sequences on the qua...

You get the best of both worlds? Integrating deep learning and traditional machine learning for breast cancer risk prediction.

Breast Cancer is the most commonly diagnosed cancer worldwide. While screening mammography diminishe...

Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection.

Employing two standard mammography views is crucial for radiologists, providing comprehensive insigh...

Habitat-Based Radiomics for Revealing Tumor Heterogeneity and Predicting Residual Cancer Burden Classification in Breast Cancer.

PURPOSE: To investigate the feasibility of characterizing tumor heterogeneity in breast cancer ultra...

Integrating Eye Tracking With Grouped Fusion Networks for Semantic Segmentation on Mammogram Images.

Medical image segmentation has seen great progress in recent years, largely due to the development o...

Weakly supervised multi-modal contrastive learning framework for predicting the HER2 scores in breast cancer.

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for prognosis and predicti...

A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things.

With bio-medical wearables becoming an essential part of Internet of Medical things (IoMT) for monit...

Hybrid transformer-based model for mammogram classification by integrating prior and current images.

BACKGROUND: Breast cancer screening via mammography plays a crucial role in early detection, signifi...

Machine learning models for water safety enhancement.

Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial ra...

Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly pr...

Exploring the Social Media Discussion of Breast Cancer Treatment Choices: Quantitative Natural Language Processing Study.

BACKGROUND: Early-stage breast cancer has the complex challenge of carrying a favorable prognosis wi...

Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in ...

Semiautomated Extraction of Research Topics and Trends From National Cancer Institute Funding in Radiological Sciences From 2000 to 2020.

PURPOSE: Investigators and funding organizations desire knowledge on topics and trends in publicly f...

Unrolled deep learning for breast cancer detection using limited-view photoacoustic tomography data.

Photoacoustic tomography (PAT) has emerged as a promising imaging modality for breast cancer detecti...

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.

To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular t...

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