Found 64,920 clinical trials
Village-Based Management of Chronic Cardiovascular Disease in Qu Jiang Elderly Population Registry: The BOUQUET Cohort Study
This is a prospective observational cohort study conducted in Qujiang District, Zhejiang Province, China, aiming to evaluate the effectiveness of a comprehensive management program for elderly patients with chronic cardiovascular diseases (CVDs). The program integrates pharmacological treatment, lifestyle modification, health education, and long-term follow-up, with enhanced monitoring using 7-day ECG …
Early Severe Illness TrAnslational BioLogy InformaticS in Humans
Advanced stages of the response to life-threatening infection, severe trauma, or other physiological insults often lead to exhaustion of the homeostatic mechanisms that sustain normal blood pressure and oxygenation. These syndromic presentations often meet the diagnostic criteria of sepsis and/or the acute respiratory distress syndrome (ARDS), the two most common …
Deep Learning for Automated Discrimination Between Stage T1-T2 and T3 Renal Cell Carcinoma on Contrast-Enhanced CT
This study aims to develop and validate a contrast-enhanced CT-based deep-learning model for automatic and accurate preoperative discrimination between T1-T2 and T3 renal cell carcinoma. By quantifying the model's diagnostic performance on an independent test set-using AUC, sensitivity, specificity, positive/negative predictive values, and decision-curve analysis-we will establish a decision-support tool …
Mobile Lung Cancer Screening
Lung cancer screening using low-dose CT (LDCT) has been shown to reduce mortality in high-risk populations. In 2022, the French National Cancer Institute (INCa) issued guidelines recommending screening for individuals aged 50-74 with a history of heavy smoking, including current smokers or those who quit less than 15 years ago. …
ALG-LungCancerRegistry (SAFRO2202)
SAFRO 2202 ALG-Lung Cancer Registry is a prospective, multicenter, non-interventional observational study conducted across 21 public and university hospitals in Algeria. The objective is to characterize the epidemiological, clinical, pathological, molecular, and therapeutic features of patients diagnosed with lung cancer, including non-small cell lung cancer (NSCLC), small cell lung cancer …
Enhanced Valves Interventions and Safe AI Generated End Results
This non-interventional study aims to use artificial intelligence to improve the prediction of transcatheter heart valve interventions and optimize patient outcomes. It is based on the analysis of retrospective data from various specialized centers worldwide.
Novel Sepsis Sub-phenotypes Based on Trajectories of Vital Signs
Sepsis is a dysregulated host response to infection resulting in organ dysfunction. Over the past three decades, more than 30 pharmacological therapies have been tested in >100 clinical trials and have failed to show consistent benefit in the overall population of patients with sepsis. The one-size-fits-all approach has not worked. …
New AI-based Technologies in Nuclear Medicine
The study aims to identify and predict radiopharmaceutical extravasation events using new semi-quantitative parameters and machine learning models. It involves dose rate measurements to develop metrics for real-time monitoring. It also investigates the correlation between extravasation and SUV correction in PET/CT diagnostics, providing an estimate of the correction factor necessary …
Development of a Non-invasive IVD for Endometrial Cancer Screening on High-risk Populations
CYTOMARK, a non-invasive in vitro diagnostic (IVD) test measuring a defined panel of protein biomarkers in cervical fluid, can accurately detect endometrial cancer in both symptomatic and asymptomatic women at high risk for the disease. The aim of the study consists in validating CYTOMARK's ELISA test, creating and freezing an …
EXoPERT EMERALD Clinical Study
Invitro diagnostic test for multiple cancer diagnosis for patients with early-stage cancers by analyzing surface-enhanced Ramen spectroscopy (SERS) profiles of extracellular vesicles (EV) using artificial intelligence.
