Latest AI and machine learning research in lung cancer for healthcare professionals.
Accurate survival prediction in non-small cell lung cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Multimodal deep learning (MDL) can improve precision prognosis, but small cohorts and missing modalities limit its clinical applicability, as conventional approaches enforce complete-case filtering or imputation. We present a missing-aware multimodal survival ...
BACKGROUND: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) often has an insidious onset with few or no respiratory symptoms, so early disease may be overlooked. Timely diagnosis and monitoring are therefore crucial. High-resolution computed tomography (HRCT) is the reference standard for RA-ILD, but cost and radiation limit its use as a routine screening tool. Several lower-cos...
INTRODUCTION: Dynamic Digital Radiography (DDR) is a novel bedside imaging modality that enables real-time visualization of pulmonary motion with mini...
INTRODUCTION: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis ...
BACKGROUND: Gene-wise intratumor heterogeneity (ITH), defined as spatial variability in the expression of individual genes across tumor regions, remai...
Atherosclerosis (AS) is a common complication of lung adenocarcinoma (LUAD), but its underlying mechanisms in LUAD remain unclear. This study aimed to...
The FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) mission will provide, for the first time, systematic far-infrared spectral me...
BACKGROUND: Population-scale radiation exposure assessment during radiological emergencies is hindered by the slow and costly nature of current method...
BACKGROUND: Pancreatic diseases, including diabetes, pancreatic ductal adenocarcinoma, pancreatitis, and cystic fibrosis, impose a substantial clinica...
BACKGROUND: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality, largely due to frequent metastasis to the brain and bon...
Efforts to create rapid, non-invasive, and reliable cancer diagnostics have increasingly focused on extracellular vesicles (EVs), nanoscale carriers o...
Immune checkpoint inhibitors (ICIs) benefit only a subset of patients with metastatic non-small cell lung cancer (NSCLC), but current selection relies...
Reirradiation (reRT) has become an essential therapeutic option for selected patients with locoregional recurrences, when surgery or systemic therapie...
PURPOSE: To develop and validate a multimodal deep learning framework that integrates clinical metadata with [18F]FDG PET/CT imaging to resolve overla...
Liquid crystal monomers (LCMs) are emerging contaminants whose system-level toxicity mechanisms remain poorly understood. Here, we developed a pathway...
OBJECTIVE: Phase gating is a critical technique to mitigate tumor motion during radiotherapy, particularly in spot-scanned particle therapy (SSPT) whe...
Artificial intelligence (AI) is transforming segmentation tasks in radiotherapy, but model reliability remains a critical concern, particularly for tu...
Histologically stained tissue sections are considered the gold standard for studying microscopic anatomy and diagnosing disease in clinical practice. ...
OBJECTIVES: To construct and validate a model based on clinical characteristics and magnetic resonance imaging (MRI) radiomics to predict 1-year effic...
BACKGROUND: Adolescent idiopathic scoliosis (AIS) affects 2-3% of adolescents. Current screening relies on X-rays, which limits large-scale applicatio...