Guangzhou, Guangdong Province, China Clinical Trials
A listing of Guangzhou, Guangdong Province, China clinical trials actively recruiting patients volunteers.
Found 1,327 clinical trials
Differentiation of Benign and Malignant Pulmonary Nodules by Volatile Organic Compounds in Human Exhaled Breath
The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound (VOC) markers. This model aims to accurately differentiate benign from malignant nodules in individuals harboring pulmonary nodules. The primary objectives it strives to accomplish are: To assess the diagnostic accuracy …
Development and Prospective Validation of a Digital Pathology-based Artificial Intelligence Diagnostic Model for Pan-cancer Lymphatic Metastasis
The goal of this diagnostic test is to develop an artificial intelligence (AI)-based pan-cancer universal diagnostic model for detecting pathological lymph node metastasis (LNM), and prospectively evaluate its apllication value in the real-world clinical practice. Investigators will compare the diagnostic performance (sensitivity, specificity, etc.) of the AI model and routine …
Non-invasive Tools for PSVD Diagnosis
Patients treated with platinum-based chemotherapy drugs have the probability of developing PSVD. The diagnosis of PSVD depends on liver biopsy. In addition, the level of portal vein pressure has guiding value in the diagnosis and prognosis of PSVD. Many studies have shown that liver and spleen stiffness have high accuracy …
Real-World Study on Chinese Medicine for Treating Chikungunya Fever
This study aims to evaluate the effectiveness and safety of Chinese Medicine-used alone or combined with Western medicine-in treating chikungunya fever, a mosquito-borne viral disease causing fever, rash, and severe joint pain. With recent outbreaks in China (including over 3,000 cases in Foshan, Guangdong) and no specific antiviral treatment available, …
Analysis of Exploring Optimized Sequential Treatment Strategies of Antibody-Drug Conjugates (ADCs) in HER2-Low-Expressing Breast Cancer
This study retrospectively analyzes the clinical data of HER2-low breast cancer (IHC 1+/2+ and FISH-negative) patients treated with sequential antibody-drug conjugates (ADCs). Key variables include patient demographics, tumor characteristics, ADC regimens (e.g., trastuzumab deruxtecan, sacituzumab govitecan), treatment sequencing, survival outcomes, and safety profiles. Genomic data (e.g., HER2 expression dynamics, TROP2 …
AI-Driven Prediction of Biological Age With EHR
This is a multi-center, retrospective clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for predicting biological age using electronic health records (EHR). The study will analyze various health data points, including medical history, laboratory results, and clinical observations, to estimate the biological age of …
Pipeline Embolization for Intracranial Aneurysms
This study collected the clinical, laboratory, and imaging data from patients with intracranial aneurysms, who underwent Pipeline implantation. The purpose of this study is to observe the safety, effcacy, and haemodynamics after Pipeline embolization.
Observation Study on Reducing the Risk of Liver Cancer Associated With Hepatitis B (Zhiyuan) Project.
This study is a multicenter, prospective, observational real-world study designed to investigate and analyze the current treatment patterns of chronic hepatitis B (CHB) across 200 hospitals in China. By comparing patient outcomes under different therapeutic regimens, it aims to provide high-quality evidence-based medical data to optimize CHB treatment strategies and …
Early Diagnosis and Prediction of Maternal and Neonatal Diseases:
This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for identifying maternal and neonatal diseases, leveraging multimodal health data.
Prospective Pathology Foundation Models
Histopathology remains the gold standard for disease diagnosis, yet faces challenges including pathologist shortages and diagnostic model limitations. This underscores the critical need to develop deep learning-based pathology foundation models integrating prospective imaging and clinical data. Such models would enhance diagnostic accuracy and efficiency, enabling tumor grading, histo-molecular classification, and …
