Latest AI and machine learning research in lung cancer for healthcare professionals.
For identifying natural trends, hotspots, hazardous areas, and mitigating potential health risk to the public and environment, spatial analysis of radiation levels is crucial. Machine learning models' implementation for prediction of background radiation levels and anomaly detection can bring a revolutionary change in radiation monitoring. Also, emergency evacuation routes with minimum radiation e...
Distinguishing pancreatic ductal adenocarcinoma (PDAC) from mass-forming pancreatitis (MFP) is challenging due to imaging mimicry and reader-dependent variability. PancDS is developed as a biomimetic pancreatic decision-support system that integrates clinical predictors, a radiomics signature, and self-developed deep features (PANet). PancDS is enabled by TriFusionNet, an adaptive fusion strategy ...
Preeclampsia (PE) remains a leading cause of maternal and perinatal mortality worldwide, and the combined use of Shuangjiang Decoction with Labetalol ...
PURPOSE: Nuclear emergency medical rescue is a critical component of the nuclear emergency response system, playing a vital role in safeguarding publi...
PURPOSE: Predictive biomarkers of response to immune checkpoint inhibitors (ICI) remain poorly defined in patients with non-small cell lung cancer (NS...
OBJECTIVE: Radiogenomics aims to non-invasively predict tumour genotypes from imaging, but most studies assume molecular homogeneity by assigning a si...
Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to treatment resistance and an immunosuppressive, fibrotic microenvironment. Ferrop...
PURPOSE: To investigate the feasibility of non-invasively identifying bone marrow involvement (BMI) in follicular lymphoma (FL) using baseline 18F-FDG...
Pterygium is a common ocular surface disorder, with its prevalence strongly correlated to ultraviolet (UV) exposure in geographic regions. Epidemiolog...
Contrast-enhanced CT is commonly used in the evaluation of hepatic metastatic lesions. This prospective study aimed to assess the capability of artifi...
PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...
INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems a...
BACKGROUND: Although an artificial intelligence-driven three-dimensional reconstruction system (AI-3D) facilitates preoperative planning, its impact o...
BACKGROUND: Overscanning is a common issue in CT planning, leading to unnecessary radiation exposure. PURPOSE: To develop a deep learning model to seg...
BACKGROUND: Current clinical guidelines mandate routine evaluation of anaplastic lymphoma kinase (ALK) rearrangement in lung adenocarcinoma prior to A...
PURPOSE: Detection of radiation-induced temporal lobe injury (RTLI) at the earliest radiologically detectable stage is important for timely interventi...
BACKGROUND: Artificial intelligence (AI) is considered to be a leading technology in radiation medical physics, which has the potential for improving ...
Glioblastoma is a highly aggressive primary brain tumor with near-universal recurrence despite maximal safe resection followed by standard chemoradiat...
Acute kidney injury (AKI) is common in the intensive care unit (ICU), and fixed creatinine thresholds may miss clinically relevant dynamics. We tested...
BACKGROUND: Diabetic foot ulcers (DFUs) represent a severe chronic complication of diabetes and are characterized by persistent impairment of wound he...