Lung Cancer

Unraveling the molecular landscape of chronic radiation injury: From oxidative stress signaling to translational modeling (Review).

The expanding footprint of human radiation exposure, driven by advances in interventional diagnostics, the resurgence of the nuclear industry and the deep‑space exploration, has necessitated a paradigm shift from understanding acute syndromes to the biological effects of chronic, low‑dose‑rate irradiation. Unlike acute injury, chronic radiation injury (CRI) is a distinct biological entity characte...

Integration of single-cell regulon atlas and bulk RNA-seq for individualized prognostic prediction in stomach adenocarcinoma.

Transcriptional regulators reflect cellular heterogeneity and are key for prognostic modeling. Given the poor prognosis of stomach adenocarcinoma (STAD), regulator-derived signatures are vital for risk stratification. Using multi-stage scRNA-seq data, we delineated the transcriptional regulatory landscape of STAD and identified Helicobacter pylori-associated epithelial heterogeneity in intestinal ...

Deciphering the multi-target mechanism of Magnolia officinalis in irritable bowel syndrome with diarrhea: A combined network pharmacology, machine learning, and in vivo validation study.

BACKGROUND: The bark of Magnolia officinalis Rehder & E. Wilson, used in TCM for abdominal distension, pain, and diarrhea, aligns with IBS-D symptoms....

Longitudinal Plasma Proteomics Reveals an Immuno-thrombotic Signature that Predicts Radiation Pneumonitis in Lung Cancer.

PURPOSE: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy, often poorly predicted by static clinical and dosimetric ...

Uric Acid to HDL-C Ratio as a Novel Biomarker for Sarcopenia: A National Study with Machine Learning Insights.

BACKGROUND: Sarcopenia is a major age-related health burden. Although the uric acid to high-density lipoprotein cholesterol ratio (UHR) has been linke...

Decoding the role of polyamine metabolism in lung adenocarcinoma prognosis: A triangulated approach combining transcriptome, single-cell and Mendelian randomization analyses.

The progression of lung adenocarcinoma (LUAD) is influenced by polyamine metabolism, which modulates antitumor immunity, although the underlying mecha...

Predicting 2-Year Overall Survival in NSCLC from CT Scans Using 2D CNNs and Soft Attention.

Accurate overall survival (OS) prediction in non-small cell lung cancer (NSCLC) is crucial but challenging due to high-dimensional 3D computed tomogra...

Machine Learning Models for Predicting Mortality Risk and Survival Time in Lung Cancer Patients Treated with EGFR-TKIs.

This study develops machine learning models to predict patient mortality and estimate survival time using electronic health record (EHR) data from thr...

Generating synthetic CT from MR images for radiation-free computer-assisted quantification of hip morphology.

OBJECTIVES: To compare MR image-based synthetic CT (sCT) with conventional CT for computer-assisted quantification of hip morphology by evaluating oss...

Machine learning and artificial intelligence in liquid biopsy-based early detection of pancreatic cancer: a scoping review.

Pancreatic ductal adenocarcinoma (PDAC) presents as a cancer with an especially poor prognosis, largely due to the challenges surrounding its early di...

Preoperative identification of tumor deposits in rectal cancer using a transformer-based multimodal fusion model: a multicenter retrospective study.

OBJECTIVE: To develop and validate a transformer-based deep learning-radiomics model for the non-invasive preoperative discrimination of tumor deposit...

Dynamic Bayesian networks to predict loss of kidney function: a cross-institution use case in a large cohort with or at-risk of CKD.

BACKGROUND: Substantial loss of kidney function, measured as ≥40% decline in estimated glomerular filtration rate (eGFR) within a 2-year period, is as...

Relationship between the diagnostic probability of chronic kidney disease calculated using artificial intelligence-enhanced electrocardiography and the incidence of cardiovascular events.

AIMS: A low estimated glomerular filtration rate (eGFR) is the primary diagnostic criterion for chronic kidney disease (CKD), a known risk factor for ...

Xiao Zhen Fang mitigates cutaneous toxicity by inhibiting PANoptosis: Insights from untargeted metabolomics and transcriptomics.

BACKGROUND: Epidermal growth factor receptor (EGFR) inhibitors and other targeted therapies frequently cause cutaneous toxicities, impairing patient q...

RADIANT: A fully configurable radiotherapy dose prediction framework.

Treatment planning is a multi-disciplinary effort that requires medical decision-making, specialized training, and access to specialized software. Rec...

A neural network embedding the linear-quadratic model for improved prediction of cellular response to ion beam exposure.

Predicting biological responses to ionizing radiation is challenging due to the complex, multi-scale mechanisms involved. Traditional machine learning...

Machine learning-based risk prediction model for postoperative acute kidney injury in surgical patients with chronic kidney disease (CKD): development, validation, and SHAP-based explainability.

This study aimed to develop machine learning models to predict postoperative acute kidney injury (AKI) in surgical patients with pre-existing chronic ...

Clinical knowledge constrained multi-task learning framework for breast cancer diagnosis using ultrasound videos.

Ultrasound is widely used in breast cancer diagnosis due to its cost-effectiveness, non-invasiveness, and radiation-free properties. Computer-aided di...

Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.

BACKGROUND: Accurate and timely disease detection is essential in modern healthcare. Conventional imaging methods such as computed tomography (CT), ma...

Multicenter validation and randomized crossover reader evaluation of deep learning-assisted tri-sequence three-dimensional MRI segmentation for hypopharyngeal tumor.

BACKGROUND AND PURPOSE: Accurate MRI-based target delineation for hypopharyngeal squamous cell carcinoma (HPSCC) is clinically important but expertise...