{"publication_id":"93653872-d78c-420f-b226-287abf988452","content_hash":"sha256:3150e1575c8c8cc2526985b33ec79a21c1f89f0252a4097c9ec7763fb795bc4a","nodes":[{"id":"93653872-d78c-420f-b226-287abf988452","type":"publication","title":"related_macular: one bounded, context-dependent signal across receipts"},{"id":"claim_1","type":"claim","text":"Across retrieved fact-level receipts for related_macular, which endpoints show directionally favorable versus null/non-convergent signals, and what matched PICO remains untested?"},{"id":"claim_2","type":"claim","text":"null/non-convergent or other/mixed: the extracted fact is null, mixed, or not directionally interpretable."},{"id":"claim_3","type":"claim","text":"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)."},{"id":"claim_4","type":"claim","text":"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."},{"id":"claim_5","type":"claim","text":"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."},{"id":"source_1","type":"source","study":"Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.","year":2014,"doi":"10.1364/boe.5.003568","url":"https://doi.org/10.1364/boe.5.003568","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_2","type":"source","study":"A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images","year":2024,"doi":"10.1038/s41598-024-52131-2","url":"https://doi.org/10.1038/s41598-024-52131-2","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_3","type":"source","study":"Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening","year":2024,"doi":"10.1038/s41746-024-01018-7","url":"https://doi.org/10.1038/s41746-024-01018-7","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_4","type":"source","study":"Unsupervised Super-Resolution of OCT Images Using Generative Adversarial Network for Improved Age-Related Macular Degeneration Diagnosis","year":2020,"doi":"10.1109/jsen.2020.2985131","url":"https://doi.org/10.1109/jsen.2020.2985131","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_5","type":"source","study":"Towards automatic detection of age-related macular degeneration in retinal fundus images","year":2010,"doi":"10.1109/iembs.2010.5627289","url":"https://doi.org/10.1109/iembs.2010.5627289","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"}],"edges":[{"from":"93653872-d78c-420f-b226-287abf988452","to":"claim_1","type":"contains_claim"},{"from":"93653872-d78c-420f-b226-287abf988452","to":"claim_2","type":"contains_claim"},{"from":"93653872-d78c-420f-b226-287abf988452","to":"claim_3","type":"contains_claim"},{"from":"93653872-d78c-420f-b226-287abf988452","to":"claim_4","type":"contains_claim"},{"from":"93653872-d78c-420f-b226-287abf988452","to":"claim_5","type":"contains_claim"}],"screening":{"identified":5,"screened":5,"excluded":0,"included":5,"included_or_retained":5,"flow":["identified","screened","excluded_with_reasons","included"],"wording":"5 candidate receipts retained after source retrieval, deduplication, and topic filtering. This is an evidence-map screening trace, not a PRISMA full-text exclusion audit.","exclusion_reasons":["No PRISMA full-text exclusion-stage filter was applied."]}}