View clinical trials related to Pathology.
Filter by:To collect lab data from capillary and venous blood specimens for use in analytical research studies to support the development and validation of laboratory procedures.
This study seeks to develop a deep-learning-based intelligent predictive model for the efficacy of neoadjuvant chemotherapy in gastric cancer patients. By utilizing the patients' CT imaging data, biopsy pathology images, and clinical information, the intelligent model will predict the post-neoadjuvant chemotherapy efficacy and prognosis, offering assistance in personalized treatment decisions for gastric cancer patients.
This project focuses on researching chronic rhinosinusitis in patients, employing image processing techniques and molecular biology methods to jointly determine the research objectives: 1. Investigating heterogeneity. 2. Developing an intelligent assessment model. 3. Creating a visual tool for diagnosis and prognosis.
This study is one of Eastern Cooperative Thoracic Oncology Projects (ECTOP-1016). The goal of this clinical trial is to confirm the concordance rate between intra-operative frozen section pathological diagnosis and post-operative paraffin embedded pathological diagnosis, and use this result to guide surgical treatment for early stage (cT1N0M0) lung adenocarcinomas.
This study is one of Eastern Cooperative Thoracic Oncology Projects (ECTOP-1015). The goal of this clinical trial is to confirm the concordance rate between intra-operative frozen section pathological diagnosis and post-operative paraffin embedded pathological diagnosis, and use this result to guide surgical treatment for early stage (cT1N0M0) lung adenocarcinomas.
This study is one of Eastern Cooperative Thoracic Oncology Projects (ECTOP-1014). The goal of this clinical trial is to confirm the concordance rate between intra-operative frozen section pathological diagnosis and post-operative paraffin embedded pathological diagnosis, and use this result to guide surgical treatment for early stage (cT1N0M0) lung adenocarcinomas.
The OLGIM staging system is highly recommended for a comprehensive assessment of GIM severity to evaluate patients' gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible due to a serious shortage of pathologists compared with the large number of gastric cancer screening population. We plan to develop a Digital Pathology artificial intelligence diagnosis system (DPAIDS), to automatically identify tumor areas in whole slide images(WSI) and quickly and accurately quantify the severity of intestinal metaplasia according to the proportion of intestinal metaplasia areas.
Since 1991, the Banff classification has been the gold standard for defining antibody-mediated rejection (AMR) and T-cell mediated rejection (TCMR), thereby guiding the treatment and management of transplant recipients. Starting from a pure histological approach, the classification has moved over the past three decades towards an integrated precision diagnosis system, which encompasses other expertise, such as immunology, immunogenetic, other basic sciences, biostatistics, data science, and artificial intelligence The counterpart of this constant refinement is that Banff rules are becoming complex to follow, with numerous possible scenarios leading to a high degree of inter-observer variability and misclassifications, which may lead to therapeutic consequences. The aims of this study are: 1. To integrate and decode all Banff rules and develop a computer-based application - the Banff Automation System - which provides automated and reproducible diagnoses 2. To validate the ability of the Banff Automation System to reclassify rejection diagnoses in multicenter cohort studies and clinical trials.
The EDEN study will make it possible to evaluate one or more development phases (from design to validation through optimization) of a method or a technique on voluntary subjects, in normal or pathological condition.
The diaphragm is the fundamental muscle of the respiratory system. The diaphragmatic dysfunction is present in 60% of critical patients at hospital admission and up to 80% after prolonged mechanical ventilation and difficult weaning. Risk factors associated with diaphragm dysfunction and atrophy are sepsis, trauma, sedatives, steroids, and muscle relaxants. The main pathology characteristics of diaphragm biopsies of mechanically ventilated patients are atrophy and a reduction in contractility, determining an impact on the clinical outcome. Shi et al. found a higher section area of the diaphragm muscle fiber in biopsies of post mortem COVID-19 patients versus negative patients, independently from days of mechanical ventilation. The hypothesis of our study is to identify different clusters of pathological presentation in post-mortem COVID-19 mechanically ventilated patients.