Breast Cancer

Breast cancer frontiers: mapping molecular signals, intelligent diagnostics, and adaptive therapies.

Breast cancer continues to be a significant worldwide health concern, requiring ongoing improvements...

Utilization of machine learning algorithms for the identification of the RLN associated prognostic model and feature biomarkers of RLN-related subtypes in breast cancer.

BACKGROUND: Breast cancer (BC) is the most common malignancy afflicting women worldwide, yet the rol...

Sorafenib nanomedicine in HCC: nano-bio interactions and combination therapies.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with s...

Predicting the Efficacy of Breast Cancer Neoadjuvant Chemotherapy Using Ultrasonography and Machine Learning.

OBJECTIVE: This study aimed to develop a machine learning model based on ultrasonography (US) and cl...

On the transfer learning behavior of domain-specific vision-language models in screening mammography.

Vision-Language models have shown remarkable performance for natural images and text. Given the homo...

Lung scintigraphy for the diagnosis of acute pulmonary embolism.

Pulmonary embolism (PE) remains a major diagnostic challenge due to its potentially life-threatening...

Amplifying image quality gain in x-ray phase contrast imaging of mastectomy samples with deep learning denoising.

Phase-contrast computed tomography (PCT) of the breast has previously been shown to produce higher-q...

Integrative multi-omics and machine learning framework identifies PRDX4 as a redox-EMT regulator and predictive marker in bone-metastatic breast cancer.

Bone metastasis is a major cause of morbidity and mortality in breast cancer, yet effective prognost...

Semi-supervised learning for dose prediction in targeted radionuclide therapy: a synthetic data study.

Objective.Accurate and personalized radiation dose estimation is crucial for effective targeted radi...

iMCN: information compression-based multimodal confidence-guided fusion network for cancer survival prediction.

The rapid development of deep learning-based computational pathology and genomics has demonstrated t...

Patient perceptions and attitudes towards the use of artificial intelligence in the symptomatic breast unit.

OBJECTIVES: Artificial intelligence (AI) has been applied in a number of breast screening settings w...

Translational and real-world evidence of trastuzumab biosimilar CT-P6 plus pertuzumab in neoadjuvant HER2-positive early breast cancer.

BACKGROUND: Data on neoadjuvant treatment with trastuzumab biosimilars, particularly CT-P6, in combi...

Domain adaptation, self-supervision, and generative augmentation enhance GNNs for breast cancer prediction.

Breast cancer presents substantial molecular heterogeneity, requiring accurate subtype classificatio...

Intratumoral and Peritumoral Fat CT‑Based Radiomics for Predicting Recurrence Risk in Non-Muscle-Invasive Bladder Cancer: A Two-Center Study.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) has a high risk of recurrence, and multiple s...

Loss of biomechanical features reveals smooth muscle disruption and disease progression in prostate cancer.

BACKGROUND: Biomechanical features show notable heterogeneity in tumor risk stratification, yet thei...

Validation of uPath HER2 dual-colour dual in-situ hybridisation image analysis tool for HER2/neu testing in breast cancer.

AIMS: HER2/neu gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical p...

Attenuation-based ultra-low-dose lung computed tomography at 0.1 mSv to 0.3 mSv effective dose in children.

BACKGROUND: Radiation dose reduction is essential in paediatric lung computed tomography (CT). Advan...

Model uncertainty estimates for deep learning mammographic density prediction using ordinal and classification approaches.

Mammographic density is associated with the risk of developing breast cancer and can be predicted us...

A prognostic signature of ferroptosis and lipid metabolism related genes predicts survival and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. There is an in...

MRI-Based peritumoral radiomics for predicting recurrence risk in ER+/HER2- breast cancer.

Machine Learning-Based Prediction of Distant Recurrence Risk and Ribociclib Treatment Effect in HR+/HER2- Early Breast Cancer Using Real-World and NATALEE Data.

PURPOSE: Despite current standard-of-care endocrine therapy, distant recurrence remains a concern fo...