Breast Cancer

Clinical and Dosimetric Impact of 2D kV Motion Monitoring and Intervention in Liver Stereotactic Body Radiation Therapy.

PURPOSE: Positional errors resulting from motion are a principal challenge across all disease sites ...

Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Liposome-based anticancer agents take advantage of the increased vascular permeability and transvasc...

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT...

Cytotoxic activity of ethyl acetate extract of on MCF7 and T47D breast cancer cells.

One of the most cancers in women that can be fatal is breast cancer. Radiation therapy, chemotherapy...

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, r...

NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions.

Deep learning neural networks (DLNN) in Artificial intelligence (AI) have been extensively explored ...

Deep learning catheter tip locations for photoacoustic-guided cardiac interventions.

SIGNIFICANCE: Interventional cardiac procedures often require ionizing radiation to guide cardiac ca...

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemothe...

Clinical service evaluation of the feasibility and reproducibility of novel artificial intelligence based-echocardiographic quantification of global longitudinal strain and left ventricular ejection fraction in trastuzumab-treated patients.

INTRODUCTION: Cardiotoxicity is a potential prognostically important complication of certain chemoth...

ASO Author Reflections: Deep-Learning Radiomics Nomogram Based on Enhanced CT to Predict the Effect of Neoadjuvant Chemotherapy on Metastatic Lymph Nodes in Locally Advanced Gastric Cancer.

Framework for Radiation Oncology Department-wide Evaluation and Implementation of Commercial Artificial Intelligence Autocontouring.

PURPOSE: Artificial intelligence (AI)-based autocontouring in radiation oncology has potential benef...

Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baselin...

Exploring Capabilities of Large Language Models such as ChatGPT in Radiation Oncology.

PURPOSE: Technological progress of machine learning and natural language processing has led to the d...

Enhancing Safety in AI-Driven Cone Beam CT-based Online Adaptive Radiation Therapy: Development and Implementation of an Interdisciplinary Workflow.

PURPOSE: The emerging online adaptive radiation therapy (OART) treatment strategy based on cone beam...

Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.

RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary res...

Current Strengths and Weaknesses of ChatGPT as a Resource for Radiation Oncology Patients and Providers.

PURPOSE: Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence program that ...

Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example.

Microplastics (MPs) and nanoplastics (NPs) are global pollutants with emerging concerns. Methods to ...

Healthcare Professional Association Agency in Preparing for Artificial Intelligence: A Multiple-Case Study of Radiation Medicine and Medical Imaging in the Canadian context.

As artificial intelligence (AI) is increasingly integrated in healthcare, it is incumbent on healthc...

Application of statistical machine learning in biomarker selection.

In the recent JAVELIN Bladder 100 phase 3 trial, avelumab plus best supportive care significantly pr...

Nomograms integrating CT radiomic and deep learning signatures to predict overall survival and progression-free survival in NSCLC patients treated with chemotherapy.

OBJECTIVES: This study aims to establish nomograms to accurately predict the overall survival (OS) a...

Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images.

BACKGROUND: Sentinel lymph node (SLN) status is a clinically important prognostic biomarker in breas...