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The purpose of this study is to develop and validate a clinical decision support system based on automated algorithms. This system can use natural language processing to extract data from patients' endoscopic reports and pathological reports, identify patients' disease types and grades, and generate guidelines based follow-up or treatment recommendations
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Artificial Intelligence support decision group | According the endoscopic reports and pathological reports, the decision support system recognise patients' disease types and grades, and generate guidelines based survilliance or treatment recommendations. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI recongnize disease and generate recommendations | Other | According the endoscopic reports and pathological reports, the decision support system recognise patients' disease types and grades, and generate guidelines based survilliance or treatment recommendations. |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic accuracy of gastric diseases with deep learning algorithm | The diagnostic accuracy of gastric diseases with deep learning algorithm | 12 month |
| The accuracy of recommentions for different disease with deep learning algorithm | The accuracy of recommentions for different disease with deep learning algorithm | 12 month |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic sensitivity of gastric diseases with deep learning algorithm | The diagnostic sensitivity of gastric diseases with deep learning algorithm | 12 month |
| The diagnostic specificity of gastric diseases with deep learning algorithm |
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Inclusion Criteria:
Exclusion Criteria:
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patients who came to Qilu Hospital of Shandong University and received endoscopy examination but not therapeutic endoscopy
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Qilu Hospital, Shandong University | Jinan | Shandong | 250012 | China |
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The diagnostic specificity of gastric diseases with deep learning algorithm
| 12 month |
| The diagnostic positive predictive value of gastric diseases with deep learning algorithm | The diagnostic positive predictive valu of gastric diseases with deep learning algorithm | 12 month |
| The diagnostic negative predictive value of gastric diseases with deep learning algorithm | The diagnostic negative predictive value of gastric diseases with deep learning algorithm | 12 month |
| The F-score of gastric diseases with deep learning algorithm | The F-score of gastric diseases with deep learning algorithm | 12 month |
| ID | Term |
|---|---|
| D005757 | Gastritis, Atrophic |
| D013274 | Stomach Neoplasms |
| ID | Term |
|---|---|
| D005756 | Gastritis |
| D005759 | Gastroenteritis |
| D005767 | Gastrointestinal Diseases |
| D004066 | Digestive System Diseases |
| D013272 | Stomach Diseases |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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