Oncology/Hematology

Breast Cancer

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

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Showing 1912-1932 of 6,175 articles
Emerging biomarkers for pancreatic cancer: from early detection to personalized therapy.

Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its poor progno...

May 2025 40348906
CAST: Time-Varying Treatment Effects with Application to Chemotherapy and Radiotherapy on Head and Neck Squamous Cell Carcinoma

Causal machine learning (CML) enables individualized estimation of treatment effects, offering cri...

Towards order of magnitude X-ray dose reduction in breast cancer imaging using phase contrast and deep denoising

Breast cancer is the most frequently diagnosed human cancer in the United States at present. Early...

[Urban Ozone Driving Factors Based on Explainable Machine Learning].

Sixteen sites in the coastal city of Qingdao, including eight national control sites, seven provinci...

May 2025 40390396
A quantitative characterization of the heterogeneous response of glioblastoma U-87 MG cell line to temozolomide.

Most cancers are genetically and phenotypically heterogeneous. This includes subpopulations of cells...

May 2025 40341226
New Strategies and Artificial Intelligence Methods for the Mitigation of Toxigenic Fungi and Mycotoxins in Foods.

The proliferation of toxigenic fungi in food and the subsequent production of mycotoxins constitute ...

May 2025 40423314
Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study.

PURPOSE: Gene expression profiles are used for decision making in the adjuvant setting in hormone re...

May 2025 40347583
Potential of artificial intelligence for radiation dose reduction in computed tomography -A scoping review.

INTRODUCTION: Artificial intelligence (AI) is now transforming medical imaging, with extensive ramif...

May 2025 40339443
Lesion-Aware Generative Artificial Intelligence for Virtual Contrast-Enhanced Mammography in Breast Cancer

Contrast-Enhanced Spectral Mammography (CESM) is a dual-energy mammographic technique that improve...

DeepSparse: A Foundation Model for Sparse-View CBCT Reconstruction

Cone-beam computed tomography (CBCT) is a critical 3D imaging technology in the medical field, whi...

OmicsCL: Unsupervised Contrastive Learning for Cancer Subtype Discovery and Survival Stratification

Unsupervised learning of disease subtypes from multi-omics data presents a significant opportunity...

Automated segmenta-on of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023

Surgery plays an important role within the treatment for neuroblastoma, a common pediatric cancer....

Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework.

Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and a...

May 2025 40249269
Development of an automated photolysis rates prediction system based on machine learning.

Based on observed meteorological elements, photolysis rates (J-values) and pollutant concentrations,...

May 2025 39481934
Innovations in artificial intelligence for pet/mr imaging: Application and performance analysis.

BackgroundThe primary challenges in PET/MR imaging include prolonged scan durations for both PET and...

May 2025 40343882
Breast Cancer Detection from Multi-View Screening Mammograms with Visual Prompt Tuning

Accurate detection of breast cancer from high-resolution mammograms is crucial for early diagnosis...

Optimizing chemoradiotherapy for malignant gliomas: a validated mathematical approach

Malignant gliomas (MGs), particularly glioblastoma, are among the most aggressive brain tumors, wi...

Radiometer Calibration using Machine Learning

Radiometers are crucial instruments in radio astronomy, forming the primary component of nearly al...

Optimizing Post-Cancer Treatment Prognosis: A Study of Machine Learning and Ensemble Techniques

The aim is to create a method for accurately estimating the duration of post-cancer treatment, par...

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