Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results
Code, duplicate map (meta_groups.csv) and out-of-fold predictions for the article Data leakage inflates smartphone conjunctival pallor anaemia detection in children: a deduplicated benchmark of colour features versus lightweight CNNs on CP-AnemiC. Includes the SHA-256 + perceptual-hash duplicate aud...
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| Autores principales: | , , , |
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| Formato: | Software |
| Lenguaje: | inglés |
| Publicado: |
2026
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| Acceso en línea: | Enlace permanente (DOI o Handle) |
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| _version_ | 1881700533246361600 |
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| author | Fran Franklin Calizaya Apaza Bisleyn de la Flor Arce Apaza Jhoel Hairton Apaza Quispe Ángel Rosendo Condori-Coaquira |
| author_browse | Bisleyn de la Flor Arce Apaza Fran Franklin Calizaya Apaza Jhoel Hairton Apaza Quispe Ángel Rosendo Condori-Coaquira |
| author_facet | Fran Franklin Calizaya Apaza Bisleyn de la Flor Arce Apaza Jhoel Hairton Apaza Quispe Ángel Rosendo Condori-Coaquira |
| author_sort | Fran Franklin Calizaya Apaza |
| collection | Producción científica |
| description | Code, duplicate map (meta_groups.csv) and out-of-fold predictions for the article Data leakage inflates smartphone conjunctival pallor anaemia detection in children: a deduplicated benchmark of colour features versus lightweight CNNs on CP-AnemiC. Includes the SHA-256 + perceptual-hash duplicate audit of CP-AnemiC (710 rows, 472 unique images), colour-feature classifiers with nested repeated cross-validation, lightweight CNNs (PyTorch/CUDA and Keras) with ONNX/TFLite FP32/FP16/INT8 export and latency measurements, SHAP and Grad-CAM explainability, WHO-2024 threshold sensitivity analysis, per-seed CNN results, figures and a CLAIM 2024 / TRIPOD+AI reporting map. Development phase of a system intended for children aged 6-59 months in Puno, Peru. |
| format | Software |
| id | openalex:W7225047859 |
| institution | UPeU |
| language | English |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| record_format | dspace |
| spelling | openalex:W7225047859Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and resultsFran Franklin Calizaya ApazaBisleyn de la Flor Arce ApazaJhoel Hairton Apaza QuispeÁngel Rosendo Condori-Coaquiraconjunctival palloranemia detectionchildren under fivesmartphone-based screeningdata leakagecolor featureslightweight convolutional neural networkmodel latencyexplainabilitySHAPGrad-CAMbenchmarkPuno, PeruDigital Imaging for Blood DiseasesArtificial Intelligence in HealthcareRetinal Imaging and AnalysisCode, duplicate map (meta_groups.csv) and out-of-fold predictions for the article Data leakage inflates smartphone conjunctival pallor anaemia detection in children: a deduplicated benchmark of colour features versus lightweight CNNs on CP-AnemiC. Includes the SHA-256 + perceptual-hash duplicate audit of CP-AnemiC (710 rows, 472 unique images), colour-feature classifiers with nested repeated cross-validation, lightweight CNNs (PyTorch/CUDA and Keras) with ONNX/TFLite FP32/FP16/INT8 export and latency measurements, SHAP and Grad-CAM explainability, WHO-2024 threshold sensitivity analysis, per-seed CNN results, figures and a CLAIM 2024 / TRIPOD+AI reporting map. Development phase of a system intended for children aged 6-59 months in Puno, Peru.Softwarehttps://doi.org/10.5281/zenodo.23851747W7225047859enZenodo (CERN European Organization for Nuclear Research)2026-11-01 |
| spellingShingle | conjunctival pallor anemia detection children under five smartphone-based screening data leakage color features lightweight convolutional neural network model latency explainability SHAP Grad-CAM benchmark Puno, Peru Digital Imaging for Blood Diseases Artificial Intelligence in Healthcare Retinal Imaging and Analysis Fran Franklin Calizaya Apaza Bisleyn de la Flor Arce Apaza Jhoel Hairton Apaza Quispe Ángel Rosendo Condori-Coaquira Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results |
| title | Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results |
| title_full | Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results |
| title_fullStr | Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results |
| title_full_unstemmed | Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results |
| title_short | Deduplicated benchmark for smartphone conjunctival anaemia detection in children (CP-AnemiC): code, duplicate map and results |
| title_sort | deduplicated benchmark for smartphone conjunctival anaemia detection in children cp anemic code duplicate map and results |
| topic | conjunctival pallor anemia detection children under five smartphone-based screening data leakage color features lightweight convolutional neural network model latency explainability SHAP Grad-CAM benchmark Puno, Peru Digital Imaging for Blood Diseases Artificial Intelligence in Healthcare Retinal Imaging and Analysis |
| topic_facet | conjunctival pallor anemia detection children under five smartphone-based screening data leakage color features lightweight convolutional neural network model latency explainability SHAP Grad-CAM benchmark Puno, Peru Digital Imaging for Blood Diseases Artificial Intelligence in Healthcare Retinal Imaging and Analysis |
| url | https://doi.org/10.5281/zenodo.23851747 |
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