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The images of patients with pancreatic cancer were collected and analyzed based on the methodes of radiomics
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| patients with pancreatic cancer | Patients with pancreatic tumors diagnosed clinically or pathologically | ||
| Participants without pancreatic cancer | Participants who judged the pancreas to be completely healthy through medical examination |
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| Measure | Description | Time Frame |
|---|---|---|
| 5-year survival rate | 1 week |
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Inclusion Criteria:
Exclusion Criteria:
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All participants willing to receive abdominal imaging could be included in this study
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37216230 | Derived | Fu N, Fu W, Chen H, Chai W, Qian X, Wang W, Jiang Y, Shen B. A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study. Int J Surg. 2023 Aug 1;109(8):2196-2203. doi: 10.1097/JS9.0000000000000469. |
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| ID | Term |
|---|---|
| D010190 | Pancreatic Neoplasms |
| ID | Term |
|---|---|
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004701 | Endocrine Gland Neoplasms |
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| D004066 |
| Digestive System Diseases |
| D010182 | Pancreatic Diseases |
| D004700 | Endocrine System Diseases |