Lung Cancer

Exploring dysregulation of cuproptosis-related genes molecular clusters and candidate biomarkers in pterygium.

Pterygium is a common ocular surface disorder, with its prevalence strongly correlated to ultraviolet (UV) exposure in geographic regions. Epidemiological investigations reveal significant demographic variations, with higher incidences observed in areas with intense UV radiation and within specific populations, notably rural individuals. Despite surgical interventions being the standard treatment,...

Artificial intelligence iterative imaging reconstruction with low-dose CT scans for hepatic metastases.

Contrast-enhanced CT is commonly used in the evaluation of hepatic metastatic lesions. This prospective study aimed to assess the capability of artificial intelligence iterative reconstruction (AIIR) in low-dose CT for detection of hepatic metastases. Thirty-two patients with hepatic metastases were enrolled and underwent dual-phase CT scans in the venous phase. Each patient received a standard-do...

Beyond eGFR and Albuminuria: Biological Pathways and Multiomics in Cardiovascular-Kidney-Metabolic Disease.

Cardiovascular-kidney-metabolic disease (CKM) represents a growing public health challenge driven by the convergence of obesity, diabetes, and cardiov...

Efficacy of short-course bevacizumab for brain tumor radiation necrosis with a volumetric analysis.

PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...

Measuring AI preparedness in health professions education: Evidence from a national survey of medical radiation science students and new graduates.

INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems a...

Artificial Intelligence-Driven Three-Dimensional Reconstruction System Reduced Unexpected Procedural Changes in Thoracic Surgery.

BACKGROUND: Although an artificial intelligence-driven three-dimensional reconstruction system (AI-3D) facilitates preoperative planning, its impact o...

TOPOS: target organ prediction on scout views for automated CT scan planning.

BACKGROUND: Overscanning is a common issue in CT planning, leading to unnecessary radiation exposure. PURPOSE: To develop a deep learning model to seg...

Deep learning-based CT radiomics for ALK rearrangement status prediction in lung adenocarcinoma.

BACKGROUND: Current clinical guidelines mandate routine evaluation of anaplastic lymphoma kinase (ALK) rearrangement in lung adenocarcinoma prior to A...

Deep learning for detection and automatic visualization of radiation-induced temporal lobe injury in nasopharyngeal carcinoma across endemic and non-endemic areas in China.

PURPOSE: Detection of radiation-induced temporal lobe injury (RTLI) at the earliest radiologically detectable stage is important for timely interventi...

The Integration of Artificial Intelligence in Radiation Medical Physics: Insights from an International Survey with Regional Variability.

BACKGROUND: Artificial intelligence (AI) is considered to be a leading technology in radiation medical physics, which has the potential for improving ...

Personalized machine learning-guided radiation dose escalation in newly diagnosed glioblastoma: prospective pilot study.

Glioblastoma is a highly aggressive primary brain tumor with near-universal recurrence despite maximal safe resection followed by standard chemoradiat...

Deep-learning time-series anomaly detection of acute kidney injury from creatinine-eGFR trajectories in the ICU.

Acute kidney injury (AKI) is common in the intensive care unit (ICU), and fixed creatinine thresholds may miss clinically relevant dynamics. We tested...

Integrative bioinformatic analysis prioritizes TIMP1 and FN1 as angiogenesis-related candidate genes in diabetic foot ulcers.

BACKGROUND: Diabetic foot ulcers (DFUs) represent a severe chronic complication of diabetes and are characterized by persistent impairment of wound he...

Deep residual network fusing CT images and clinical variables to predict lung adenocarcinoma aggressiveness.

BACKGROUND: Lung adenocarcinoma presenting as ground-glass nodules (GGNs) comprises three invasive subtypes (adenocarcinoma in situ [AIS], minimally i...

Integrative Bioinformatics, Experimental Validation, and Interpretable Machine Learning Reveal Oxyresveratrol-Mediated Protection Against Cadmium-Induced Lung Adenocarcinoma-Related Transcriptional Dysregulation.

Cadmium (Cd) is a toxic heavy metal strongly implicated in lung adenocarcinoma (LUAD) through mechanisms involving oxidative stress, epigenetic dysreg...

Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal forms of cancer, with a five-year survival rate below 10% primarily due to late...

Robot-assisted lumbar facet joint infiltration improves accuracy and reduces radiation exposure compared to the manual technique in a comparative phantom study.

Compact robotic systems offer new opportunities for spinal procedures outside the operating room, but their potential for small-scale interventions su...

Characterization of telomere-related gene subtypes in lung adenocarcinoma and their implications for prognosis and treatment.

BACKGROUND: Telomeres, located at chromosome ends, regulate cell division and maintain genomic stability. Telomere-related genes (TRGs) play essential...

Artificial neural network analysis for oxytactic microbes in hybrid nanofluid with chemical reaction and thermal radiation.

The purpose of this investigation is to assess the outcome of Oxytactic microorganism in chemical reactive flow of TiO2 + GO/water based hybrid nanofl...

Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence.

Risk stratification is an important tool in clinical decision-making, yet current approaches often fail to translate sophisticated survival analysis i...