Latest AI and machine learning research in lung cancer for healthcare professionals.
Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the accuracy of r...
BACKGROUND: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor patholog...
Automation and artificial intelligence (AI) is already possible for many radiation therapy planning ...
The effectiveness and precision of disease diagnosis and treatment have increased, thanks to develop...
OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathologic...
BACKGROUND/AIM: Heavy-ion irradiation seriously perturbs cellular homeostasis and thus damages cells...
PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a lon...
. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency a...
We attempted to determine the optimal radiation dose to maintain image quality using a deep learnin...
BACKGROUND: The Global Evaluative Assessment of Robotic Skills is a popular but ultimately subjectiv...
Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease with five predominant histolog...
Recent advances in MRI-guided radiation therapy (MRgRT) and deep learning techniques encourage fully...
Microscopic evaluation of glands in the colon is of utmost importance in the diagnosis of inflammato...
OBJECTIVE: Few studies have explored the clinical feasibility of using deep-learning reconstruction ...
Pathogenic organisms utilize iron to survive and replicate and have evolved many processes to extra...
The aim is to support the perception of artificial intelligence in the radiation therapy landscape.
PURPOSE: Deep learning reconstruction (DLR) has been recommended as useful for improving image quali...
Motion compensation in radiation therapy is a challenging scenario that requires estimating and fore...
PURPOSE: The purpose of this study was to create and evaluate deep learning-based models to detect a...
We developed a deep learning framework to accurately predict the lymph node status of patients with ...
PURPOSE: Radiation Oncology Learning Health System (RO-LHS) is a promising approach to improve the q...