Breast Cancer

Real-Time Motion Analysis With 4D Deep Learning for Ultrasound-Guided Radiotherapy.

Motion compensation in radiation therapy is a challenging scenario that requires estimating and fore...

Deep learning-based detection and classification of multi-leaf collimator modeling errors in volumetric modulated radiation therapy.

PURPOSE: The purpose of this study was to create and evaluate deep learning-based models to detect a...

Infrastructure tools to support an effective Radiation Oncology Learning Health System.

PURPOSE: Radiation Oncology Learning Health System (RO-LHS) is a promising approach to improve the q...

Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.

BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of ...

A deep learning-based interpretable decision tool for predicting high risk of chemotherapy-induced nausea and vomiting in cancer patients prescribed highly emetogenic chemotherapy.

OBJECTIVE: This study aims to develop a risk prediction model for chemotherapy-induced nausea and vo...

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medi...

Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.

OBJECTIVE: This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to pred...

Unlocking the Power of ChatGPT, Artificial Intelligence, and Large Language Models: Practical Suggestions for Radiation Oncologists.

Recent advances in artificial intelligence (AI), such as generative AI and large language models (LL...

Classification of laterality and mastectomy/lumpectomy for breast cancer patients for improved performance of deep learning auto segmentation.

Circulating Plasma Exosomal PD-L1 Predicts Prognosis of Head and Neck Squamous Cell Carcinoma After Radiation Therapy.

PURPOSE: Radiation therapy is widely used to treat head and neck squamous cell carcinoma (HNSCC). Th...

Deep Learning for Detecting BRCA Mutations in High-Grade Ovarian Cancer Based on an Innovative Tumor Segmentation Method From Whole Slide Images.

BRCA1 and BRCA2 genes play a crucial role in repairing DNA double-strand breaks through homologous r...

Enhanced breast mass mammography classification approach based on pre-processing and hybridization of transfer learning models.

BACKGROUND AND OBJECTIVE: The second most prevalent cause of death among women is now breast cancer,...

An overview of artificial intelligence in medical physics and radiation oncology.

Artificial intelligence (AI) is developing rapidly and has found widespread applications in medicine...

Deep learning-based scan range optimization can reduce radiation exposure in coronary CT angiography.

OBJECTIVES: Cardiac computed tomography (CT) is essential in diagnosing coronary heart disease. Howe...

Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics.

The tumor microenvironment (TME) plays a critical role in disease progression and is a key determina...

The Clinical Added Value of Breast Cancer Imaging Using Hybrid PET/MR Imaging.

Dedicated MR imaging is highly performant for the evaluation of the primary lesion and should regula...

Deep learning for the prediction of the chemotherapy response of metastatic colorectal cancer: comparing and combining H&E staining histopathology and infrared spectral histopathology.

Colorectal cancer is a global public health problem with one of the highest death rates. It is the s...

Reducing radiation dose in routine CT scans: an AI-driven approach with deep learning-based dual-energy CT reconstruction.

Suitability of DNN-based vessel segmentation for SIRT planning.

PURPOSE: The segmentation of the hepatic arteries (HA) is essential for state-of-the-art pre-interve...

Post-chemotherapy robot-assisted retroperitoneal lymph node dissection for metastatic germ cell tumors: safety and perioperative outcomes.

PURPOSE: To evaluate the feasibility, safety, and early oncologic outcomes after post-chemotherapy r...

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus...