Lung Cancer

Association of blood urea nitrogen to high-density lipoprotein ratio with all-cause and cardiovascular mortality in individuals with mildly reduced eGFR.

BACKGROUND: Patients with mild-to-moderate renal impairment face elevated cardiovascular risk, yet early detection tools remain limited. The Cardiovascular-Kidney-Metabolism (CKM) interplay underscores the need for integrated biomarkers. The Blood Urea Nitrogen (BUN) to High-Density Lipoprotein (HDL) cholesterol ratio (BUN/HDL) was therefore evaluated for early risk stratification. METHODS: This c...

AI-Driven Rational Design of Nanotherapeutics for Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a formidable malignancy characterized by late diagnosis, high recurrence rates, and pronounced chemoresistance. While nanoparticle-based drug delivery systems (NDDS) offer theoretical advantages over conventional therapies, their clinical translation in PDAC has been severely limited. The dense desmoplastic stroma, elevated interstitial fluid pressur...

Heterogeneous effects of preoperative beta blockers on 30-day mortality after coronary artery bypass surgery.

BACKGROUND: The role of preoperative β-blocker therapy in patients with ventricular dysfunction undergoing coronary artery bypass grafting (CABG) rema...

Improved virtual non-contrast images in liver dual-energy CT with deep learning algorithm for image reconstruction.

BACKGROUND: We aimed to explore the use of deep learning image reconstruction (DLIR) to improve virtual non-contrast (VNC) images from enhanced dual-e...

Hierarchical contrastive learning from GP-recorded and eGFR labels for CKD staging.

Chronic kidney disease staging from longitudinal clinical records is challenging because routinely recorded GP stage labels are scarce, whereas rule-b...

CLDN18 as a novel junctional biomarker enhancing multi-gene classification of pancreatic cancer.

Pancreatic adenocarcinoma (PAAD) remains one of the most lethal cancers, largely due to the lack of reliable diagnostic biomarkers. Through integrativ...

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and p...

Identifying optimal dose head CT acquisition techniques through cluster analysis from 904,209 scans.

OBJECTIVES: To identify clinically established and frequently utilized routine head computed tomography (CT) acquisition techniques in children and ad...

An Exosomal Signature for Preoperative Detection of Occult Liver Metastasis in Pancreatic Cancer.

IMPORTANCE: Early liver metastasis (early-LiM) after pancreatectomy represents an aggressive biological phenotype of pancreatic ductal adenocarcinoma ...

DNAmBERT: a transformer-based model for non-invasive cancer diagnosis using DNA sequence and methylation data.

DNA methylation alterations are early and stable hallmarks of cancer and represent promising biomarkers for non-invasive detection using circulating c...

Surface Topography and Machine Learning: Strides Towards Radiation-Free Scoliosis Assessment: A Systematic Review.

BACKGROUND: Assessment of idiopathic scoliosis (IS) relies on radiographs and measurement of coronal curve magnitude, but repeated radiation exposure ...

The role and mechanism of diosgenin glucoside in modulating megakaryopoiesis through promotion of autophagy via the AMPK/mTOR/ULK1 signaling pathway.

BACKGROUND: Radiation-induced thrombocytopenia (RIT) is a severe, dose-limiting complication of cancer radiotherapy with limited clinical management o...

Cone Beam Computed Tomography-based Lung Function Imaging using Deep Learning for Functional Image-Guided Adaptative Radiation Therapy.

PURPOSE: Recent studies indicate that lung function can change significantly during radiation therapy (RT) course. However, additional function imagin...

Improving portability of knowledge-based planning using an LLM-driven plan refinement framework in lung radiotherapy.

BACKGROUND: Knowledge-based planning (KBP) has improved the quality and efficiency of radiotherapy treatment planning. However, its broader clinical a...

Dual-view scout scans with deep learning for ultra-low dose attenuation correction in PET.

BACKGROUND: Accurate attenuation correction (AC) is essential for quantitative positron emission tomography (PET). Conventional CT-based AC provides r...

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detect...

Automating cost-effectiveness models with agentic artificial intelligence: Case study and implications for value assessment.

BACKGROUND: Health economic modeling is conceptually sophisticated but operationally repetitive and resource intensive. Recent advances in large langu...

Pulmonary ventilation images from planning CT images using deep learning on locally-advanced NSCLC patients.

BACKGROUND: Pulmonary ventilation imaging has become an increasingly important component in thoracic radiotherapy, as it is applied to functional avoi...

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morph...

Exploratory Analysis of Electrical Impedance Tomography Features Associated with Spirometric Airflow Limitation.

Introduction: Electrical impedance tomography (EIT) is a noninvasive, radiation-free imaging modality that provides real-time information on regional ...