Lung Cancer

Predicting primary resistance to third-generation EGFR-TKIs in lung adenocarcinoma using a multisource cross-modal transformer model.

The aim of this study was to investigate the utility of a multisource cross-modal Transformer (MC-Trans) model in predicting primary resistance to third-generation epidermal growth factor receptor tyrosine kinase inhibitors (3rd-EGFR-TKIs) in patients with lung adenocarcinoma. A retrospective analysis of clinical and imaging data from 222 lung adenocarcinoma patients treated with 3rd-EGFR-TKIs was...

Explainable transfer learning ensemble AI model for lung ultrasound pneumothorax detection with expert benchmark.

BACKGROUND: Lung ultrasound is essential for rapid, radiation-free bedside pneumothorax diagnosis but limited by variability in human interpretation. Key gaps include insufficiently large and diverse human datasets, inconsistent image acquisition, lack of rigorous expert benchmarking, and inadequate clinical interpretability of existing artificial intelligence models. We aimed to develop and valid...

Screening of molecular signatures from microRNA and mRNA expression profiling related to the efficacy of the antidepressant duloxetine and analysis of their regulatory relationship.

Previous clinical studies have reported that not all depressed patients respond to antidepressants. Therefore, finding potential predictive molecular ...

Noninvasive Prediction of Bone Metastasis-Free Survival in Lung Adenocarcinoma Using Interpretable CT-based Deep Learning Model.

RATIONALE AND OBJECTIVES: Preoperatively identifying patients at high risk of bone metastasis (BM) remains challenging in resectable lung adenocarcino...

Clinically Localized Prostate Cancer: AUA/ASTRO Guideline Amendment (2026).

PURPOSE: Following completion of the 2025 Update Literature Review (ULR), the American Urological Association (AUA) incorporated new evidence generate...

Machine Learning-Based Synthetic Computed Tomography Derived From Temporal Bone Magnetic Resonance Imaging.

IMPORTANCE: For diagnostics and presurgical planning in otology, both magnetic resonance imaging (MRI) and computed tomography (CT) are frequently req...

Artificial Intelligence Design for Race-Based Prostate Cancer Stage Classification With Multilayer Perceptron: Feature Selection Optimization Approach.

BACKGROUND: Prostate cancer progression exhibits significant variability influenced by biological and racial factors. DNA methylation profiling has sh...

X2Shape: CT-free 3D multi-organ reconstruction with biplanar X-rays.

Reconstructing three-dimensional (3D) anatomy from routine X-ray imaging remains a long-standing challenge, promising high accessibility and minimal r...

Epigenetic Instability-Based Metrics in Cell-Free DNA for Early Cancer Detection.

PURPOSE: Cancers present significant DNA methylation changes, which arise in a stochastic manner, marked by extensive epigenetic variation, indicative...

Augmenting Large Language Model With Prompt Engineering and Supervised Fine-Tuning in Non-Small Cell Lung Cancer Tumor-Node-Metastasis Staging: Framework Development and Validation.

BACKGROUND: Accurate tumor node metastasis (TNM) staging is fundamental for treatment planning and prognosis in non-small cell lung cancer (NSCLC). Ho...

AI triage of duodenal biopsies improves workflow.

AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopatholog...

An intelligent fusion model for Ki-67 prediction in non-small cell lung cancer: A cloud-based prediction system integrating radiomics.

BACKGROUND: The expression level of Ki-67 affects the prognosis of NSCLC patients. OBJECTIVE: Accurate preoperative prediction of Ki-67 expression in ...

Long-Term Exposure to Fine Particulate Matter and Kidney Function among Patients with Polycystic Kidney Disease.

BACKGROUND: Polycystic kidney disease (PKD) is the fourth leading cause of end-stage kidney disease. Although the condition is primarily genetic, envi...

AI-based classification of pediatric sagittal skeletal patterns using multi-view facial photographs.

OBJECTIVE: The increasing global demand to assess pediatric skeletal malocclusions poses a growing challenge, as current screening methods are depende...

Evaluation of the impact of glycolysis-related gene signatures on prognosis and therapeutic targeting in lung adenocarcinoma.

Abnormal glycolysis is one of the hallmarks of cancer and plays a significant role in its progression. This study investigates the association between...

Do AI-based contouring algorithms influence physicians in the online adaptive radiotherapy of patients with bladder cancer?

PURPOSE: In this prospective cross-over study, the precision of manual correction of the clinical target volume (CTV) during online-adaptive radiother...

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment.

BACKGROUND: Accurate prediction of early recurrence (ER) after radical resection remains a critical challenge in pancreatic ductal adenocarcinoma (PDA...

Interpretable prediction of occult lymph node metastasis in pancreatic ductal adenocarcinoma using a model fusing habitat radiomics and deep learning.

PURPOSE: To evaluate the value of integrating habitat radiomics features and deep learning features for predicting occult lymph node metastasis (OLNM)...

Digital twin applications in radiology and radiotherapy: Applications, challenges, and future perspectives.

Digital twin technology has emerged as a transformative innovation in healthcare, offering virtual replicas of physical entities at patient-level, equ...

Bone Magnetic Resonance Imaging: From Conventional Methods to AI-Driven Solutions.

With global population aging and increased life expectancy, bone diseases affect a substantial proportion of individuals worldwide, imposing a signifi...