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The current standard for anemia screening, complete blood count, presents invasiveness, infrastructure requirements and high costs, leading to serious underestimation of anemia prevalence and insufficient care for anemia patients. Here, the investigators established and validated an artificial intelligence system to achieve automatic detection of anemia based on patient-sourced images of fingernails and conjunctivae. This system has been integrated into a smartphone app to be further validated through hospital-based and population-based clinical trials.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Eligible patients for app-based anemia screening | Experimental | Device: A smartphone app for anemia screening This app can achieve automatic detection of anemia based on patient-sourced images of fingernails and conjunctivae. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| A smartphone app for anemia screening | Device | This app can achieve automatic detection of anemia based on patient-sourced images of fingernails and conjunctivae. |
|
| Measure | Description | Time Frame |
|---|---|---|
| The proportion of accurate, mistaken and missed detection of this smartphone app. | 27 months |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Zhongshan Ophthalmic Center, Sun Yat-sen University | Recruiting | Guangzhou | Guangdong | 510060 | China |
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| ID | Term |
|---|---|
| D000740 | Anemia |
| ID | Term |
|---|---|
| D006402 | Hematologic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
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