NCT06534814Recruiting
Development and Application of an Artificial Intelligence-driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis
Hebei Medical University
Source: ClinicalTrials.gov · Last updated 2 Aug 2024 · Not updated for over 12 months - ask the site whether it is still open
Brief summary (registry, in English)
The clinical trial titled "Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis" aims to enhance the detection and treatment of gastric cancer through the utilization of cutting-edge artificial intelligence (AI) technology. This study will develop an AI-driven model designed to accurately identify lymph node metastasis in patients with gastric cancer, which is crucial for staging the disease and planning effective treatment strategies. The trial will involve a multidisciplinary team of oncologists, radiologists, data scientists, and AI experts who will collaborate to create a robust and precise identification system. Participants will undergo standard diagnostic procedures, and the AI model will analyze imaging and pathological data to predict lymph node involvement. By comparing the AI model's predictions with traditional diagnostic methods, the study seeks to validate the model's accuracy and efficiency. This approach is expected to improve early detection rates, reduce diagnostic errors, and ultimately lead to better clinical outcomes for patients with gastric cancer. The successful implementation of this AI-driven model could revolutionize the current standards of care and serve as a blueprint for integrating AI technologies in other cancer diagnoses and treatments.
- Status (registry)
- Recruiting
- Study type
- Observational
- Enrollment
- 300 (estimated)
- First submitted
- 25 Jul 2024
- Start date
- 1 Jul 2024
- Primary completion date
- 31 Dec 2025
- Lead sponsor
- Hebei Medical University
- Diseases
- Gastric and esophageal cancer
- NCT number
- NCT06534814
What you commit to
- Study type: Observational
- Planned participants: 300
- From 1 Jul 2024 to the primary completion date, 31 Dec 2025
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Previous AI-Driven Diagnostic Intervention: Prior use of any AI-driven diagnostic models specifically for gastric cancer lymph node metastasis.
Other illness
- Severe Comorbid Conditions: Presence of severe comorbid medical conditions that could interfere with the study or pose additional risks.
- Mental or Cognitive Impairment: Conditions that impair the ability to provide informed consent or participate effectively in the study.
Other
- Pregnancy or Lactation: Pregnant or lactating women, due to potential risks to the fetus or infant.
- Inability to Comply: Inability or unwillingness to comply with study procedures, including follow-up visits and data collection.
Who the study is looking for
- Diagnosis of Gastric Cancer: Confirmed diagnosis of gastric cancer, either newly diagnosed or recurrent.
- Lymph Node Involvement: Suspected or confirmed involvement of lymph nodes, as indicated by imaging studies or pathology reports.
- Age: Patients aged 18 years or older.
- Performance Status: An Eastern Cooperative Oncology Group (ECOG) performance status of 0 to 2, indicating a functional status that allows participation in the study.
- Informed Consent: Ability to provide written informed consent to participate in the study.
Age in the registry: 18 years to - · Sex: All
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Department of General Surgery Coordinator of this site? Confirm its status | Shijiazhuang | China | Recruiting |
This page is information, not medical advice. Discuss any trial with your doctor.