Hebei Medical University
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 300
- 试验地点
- 1
- 主要终点
- Identification of metastatic lymph nodes
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •Pregnancy or Lactation: Pregnant or lactating women, due to potential risks to the fetus or infant.
- •Severe Comorbid Conditions: Presence of severe comorbid medical conditions that could interfere with the study or pose additional risks.
- •Previous AI-Driven Diagnostic Intervention: Prior use of any AI-driven diagnostic models specifically for gastric cancer lymph node metastasis.
- •Inability to Comply: Inability or unwillingness to comply with study procedures, including follow-up visits and data collection.
- •Mental or Cognitive Impairment: Conditions that impair the ability to provide informed consent or participate effectively in the study.
结局指标
主要结局
Identification of metastatic lymph nodes
时间窗: 2025-12-31
A prediction model based on artificial intelligence technology was constructed to accurately identify metastatic perigastric lymph nodes before surgery.
次要结局
未报告次要终点
研究者
Qun Zhao
Professor
Hebei Medical University