Study on the Construction and Application of a Large Model Corpus for Pancreatic Cancer Based on Real Clinical Cases
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 3,000
- 主要终点
- Build a high-quality dedicated large model enhanced retrieval knowledge base for pancreatic cancer with a total of no less than 3,000 cases.
研究概览
简要总结
Combining retrospective observational research with artificial intelligence data engineering. Collecting historical electronic medical record data, and through data governance and annotation by artificial medical experts, constructing a structured knowledge base.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Retrospective
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
- •Real inpatient cases of pancreatic cancer diagnosis and treatment;
- •Prioritize the inclusion of cases with MDT discussion records, difficult and complex cases, and fatal cases;
- •Possess complete electronic medical information (including but not limited to: outpatient medical records, inpatient medical records including admission records, progress notes, surgery/procedure records, nursing records, examination and test reports, doctor's orders, discharge/death records, etc.); -
排除标准
- •Cases that only underwent a brief transition in emergency/outpatient departments and did not form a closed loop of diagnosis and treatment;
- •Cases with incomplete diagnosis and treatment information and missing key indicators.
结局指标
主要结局
Build a high-quality dedicated large model enhanced retrieval knowledge base for pancreatic cancer with a total of no less than 3,000 cases.
时间窗: May 2028
Combining retrospective observational studies with AI data engineering. Collect historical electronic medical record data and, through data management and expert medical labeling, build a structured knowledge base.
3,000 Cases of Pancreatic Cancer Diagnosis and Treatment
时间窗: May 2028
次要结局
未报告次要终点
研究者
Jiang Long
Principal Investigator
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine