{"publication_id":"93653872-d78c-420f-b226-287abf988452","traces":[{"claim_id":"claim_1","claim":"Across retrieved fact-level receipts for related_macular, which endpoints show directionally favorable versus null/non-convergent signals, and what matched PICO remains untested?","candidate_sources":[{"study":"Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.","doi":"10.1364/boe.5.003568","url":"https://doi.org/10.1364/boe.5.003568"},{"study":"A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images","doi":"10.1038/s41598-024-52131-2","url":"https://doi.org/10.1038/s41598-024-52131-2"},{"study":"Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening","doi":"10.1038/s41746-024-01018-7","url":"https://doi.org/10.1038/s41746-024-01018-7"},{"study":"Unsupervised Super-Resolution of OCT Images Using Generative Adversarial Network for Improved Age-Related Macular Degeneration Diagnosis","doi":"10.1109/jsen.2020.2985131","url":"https://doi.org/10.1109/jsen.2020.2985131"},{"study":"Towards automatic detection of age-related macular degeneration in retinal fundus images","doi":"10.1109/iembs.2010.5627289","url":"https://doi.org/10.1109/iembs.2010.5627289"}]},{"claim_id":"claim_2","claim":"null/non-convergent or other/mixed: the extracted fact is null, mixed, or not directionally interpretable.","candidate_sources":[{"study":"Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.","doi":"10.1364/boe.5.003568","url":"https://doi.org/10.1364/boe.5.003568"},{"study":"A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images","doi":"10.1038/s41598-024-52131-2","url":"https://doi.org/10.1038/s41598-024-52131-2"},{"study":"Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening","doi":"10.1038/s41746-024-01018-7","url":"https://doi.org/10.1038/s41746-024-01018-7"},{"study":"Unsupervised Super-Resolution of OCT Images Using Generative Adversarial Network for Improved Age-Related Macular Degeneration Diagnosis","doi":"10.1109/jsen.2020.2985131","url":"https://doi.org/10.1109/jsen.2020.2985131"},{"study":"Towards automatic detection of age-related macular degeneration in retinal fundus images","doi":"10.1109/iembs.2010.5627289","url":"https://doi.org/10.1109/iembs.2010.5627289"}]},{"claim_id":"claim_3","claim":"Specific moderators in this bundle are outcome type (SSIM; balanced accuracy; classification accuracy; sensitivity and specificity), population/indication (16 fundus images from a clinical study (half with drusen); CF-ICGA pairs from a tertiary center; clinical-grade OCT images; fundus images across normal, intermediate AMD, geographic atrophy, and wet AMD categories; patients with dry age-related macular degeneration (AMD)), study design/evidence type (primary).","candidate_sources":[{"study":"Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.","doi":"10.1364/boe.5.003568","url":"https://doi.org/10.1364/boe.5.003568"},{"study":"A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images","doi":"10.1038/s41598-024-52131-2","url":"https://doi.org/10.1038/s41598-024-52131-2"},{"study":"Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening","doi":"10.1038/s41746-024-01018-7","url":"https://doi.org/10.1038/s41746-024-01018-7"},{"study":"Unsupervised Super-Resolution of OCT Images Using Generative Adversarial Network for Improved Age-Related Macular Degeneration Diagnosis","doi":"10.1109/jsen.2020.2985131","url":"https://doi.org/10.1109/jsen.2020.2985131"},{"study":"Towards automatic detection of age-related macular degeneration in retinal fundus images","doi":"10.1109/iembs.2010.5627289","url":"https://doi.org/10.1109/iembs.2010.5627289"}]},{"claim_id":"claim_4","claim":"The selected receipts group because each carries a fact-level extraction for related_macular; they separate by context (human clinical/observational and other source context) and endpoint, so they are not interchangeable evidence for one pooled claim.","candidate_sources":[{"study":"Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.","doi":"10.1364/boe.5.003568","url":"https://doi.org/10.1364/boe.5.003568"},{"study":"A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images","doi":"10.1038/s41598-024-52131-2","url":"https://doi.org/10.1038/s41598-024-52131-2"},{"study":"Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening","doi":"10.1038/s41746-024-01018-7","url":"https://doi.org/10.1038/s41746-024-01018-7"},{"study":"Unsupervised Super-Resolution of OCT Images Using Generative Adversarial Network for Improved Age-Related Macular Degeneration Diagnosis","doi":"10.1109/jsen.2020.2985131","url":"https://doi.org/10.1109/jsen.2020.2985131"},{"study":"Towards automatic detection of age-related macular degeneration in retinal fundus images","doi":"10.1109/iembs.2010.5627289","url":"https://doi.org/10.1109/iembs.2010.5627289"}]},{"claim_id":"claim_5","claim":"The signal is purely descriptive of effect-direction heterogeneity; it cannot support even a weak causal or comparative-efficacy inference, and pooling across these PICOs would be inappropriate.","candidate_sources":[{"study":"Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.","doi":"10.1364/boe.5.003568","url":"https://doi.org/10.1364/boe.5.003568"},{"study":"A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images","doi":"10.1038/s41598-024-52131-2","url":"https://doi.org/10.1038/s41598-024-52131-2"},{"study":"Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening","doi":"10.1038/s41746-024-01018-7","url":"https://doi.org/10.1038/s41746-024-01018-7"},{"study":"Unsupervised Super-Resolution of OCT Images Using Generative Adversarial Network for Improved Age-Related Macular Degeneration Diagnosis","doi":"10.1109/jsen.2020.2985131","url":"https://doi.org/10.1109/jsen.2020.2985131"},{"study":"Towards automatic detection of age-related macular degeneration in retinal fundus images","doi":"10.1109/iembs.2010.5627289","url":"https://doi.org/10.1109/iembs.2010.5627289"}]}]}