Lung Cancer

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 diagnosis. Liquid biopsy has emerged as a promising, noninvasive method for screening across a variety of cancers. This approach is limited, however, by the extensive heterogeneity of biological samples, a challenge that teams are looking to address us...

Half-dose contrast media protocol using 70 kVp abdominal dynamic CT with super-resolution deep learning reconstruction: Evaluation of image quality and contrast performance.

OBJECTIVE: To evaluate contrast enhancement and image quality in 70 kVp abdominal dynamic CT using super-resolution deep learning reconstruction (SR-DLR) with reduced iodine contrast media (CM). METHODS: A total of 600 patients who underwent abdominal dynamic CT using SR-DLR were retrospectively investigated (estimate glomerular filtration rate [eGFR] ≤ 45 mL/min/1.73 m2, 70 kVp, iodine 300 mgI/kg...

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...

Advanced Data Analytics and Machine Learning for Geospatial Interpolation, Anomaly Detection, Background Prediction and Emergency Evacuation Routing in Real-Time Radiation Monitoring System.

For identifying natural trends, hotspots, hazardous areas, and mitigating potential health risk to the public and environment, spatial analysis of rad...

PancDS in Real-World Practice: A Prospective Multicenter Validation of a Clinical Decision-Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis.

Distinguishing pancreatic ductal adenocarcinoma (PDAC) from mass-forming pancreatitis (MFP) is challenging due to imaging mimicry and reader-dependent...

Network pharmacology and bioinformatics study of Shuangjiang decoction and labetalol hydrochloride in the treatment of preeclampsia in pregnancy.

Preeclampsia (PE) remains a leading cause of maternal and perinatal mortality worldwide, and the combined use of Shuangjiang Decoction with Labetalol ...

Radiation biomarker screening and dose reconstruction based on machine learning.

PURPOSE: Nuclear emergency medical rescue is a critical component of the nuclear emergency response system, playing a vital role in safeguarding publi...

Clinical outcomes and predictors of response to PD-(L)1 blockade in patients with NSCLC without actionable genomic alterations who never used tobacco.

PURPOSE: Predictive biomarkers of response to immune checkpoint inhibitors (ICI) remain poorly defined in patients with non-small cell lung cancer (NS...

Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.

OBJECTIVE: Radiogenomics aims to non-invasively predict tumour genotypes from imaging, but most studies assume molecular homogeneity by assigning a si...

Integrative multi-omics analysis identifies a core ferroptosis signature and validates resveratrol as a novel inducer in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to treatment resistance and an immunosuppressive, fibrotic microenvironment. Ferrop...

An interpretable PET/CT-based radiomic-clinical model for predicting bone marrow involvement in follicular lymphoma: comparison of pelvic and spine-pelvis VOI frameworks.

PURPOSE: To investigate the feasibility of non-invasively identifying bone marrow involvement (BMI) in follicular lymphoma (FL) using baseline 18F-FDG...