{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:QVPHHL5TVH4XP2Q57WIVLAG4TY","short_pith_number":"pith:QVPHHL5T","schema_version":"1.0","canonical_sha256":"855e73afb3a9f977ea1dfd915580dc9e0a4ed7dec0118a1d60c69f81073b918e","source":{"kind":"arxiv","id":"2501.01960","version":1},"attestation_state":"computed","paper":{"title":"GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split Attention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.GR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Feng Liu, Jiahao Qin","submitted_at":"2024-12-07T07:02:16Z","abstract_excerpt":"Electrocardiogram (ECG) analysis plays a crucial role in diagnosing cardiovascular diseases, but accurate interpretation of these complex signals remains challenging. This paper introduces a novel multimodal framework(GAF-FusionNet) for ECG classification that integrates time-series analysis with image-based representation using Gramian Angular Fields (GAF). Our approach employs a dual-layer cross-channel split attention module to adaptively fuse temporal and spatial features, enabling nuanced integration of complementary information. We evaluate GAF-FusionNet on three diverse ECG datasets: EC"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2501.01960","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-07T07:02:16Z","cross_cats_sorted":["cs.AI","cs.GR","cs.LG"],"title_canon_sha256":"6672eb8043a76ebf02df7c189b6ce0641ed8f0587955073dfa4a5d4b7bb85c6c","abstract_canon_sha256":"03643003e37f679e4fdf1d83d5206923ad715650927510d39dc8652cad151360"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:56:59.496618Z","signature_b64":"Hw0VnpjfkbDHQJAvIQIs5ZDimYsV74zdvJZL7n94o75SFpkkzbtB0mPcpDXPq8yfMqrcnRI0+f+O4ynj0YwKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"855e73afb3a9f977ea1dfd915580dc9e0a4ed7dec0118a1d60c69f81073b918e","last_reissued_at":"2026-07-05T09:56:59.496090Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:56:59.496090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split Attention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.GR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Feng Liu, Jiahao Qin","submitted_at":"2024-12-07T07:02:16Z","abstract_excerpt":"Electrocardiogram (ECG) analysis plays a crucial role in diagnosing cardiovascular diseases, but accurate interpretation of these complex signals remains challenging. This paper introduces a novel multimodal framework(GAF-FusionNet) for ECG classification that integrates time-series analysis with image-based representation using Gramian Angular Fields (GAF). Our approach employs a dual-layer cross-channel split attention module to adaptively fuse temporal and spatial features, enabling nuanced integration of complementary information. We evaluate GAF-FusionNet on three diverse ECG datasets: EC"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.01960","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.01960/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2501.01960","created_at":"2026-07-05T09:56:59.496161+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.01960v1","created_at":"2026-07-05T09:56:59.496161+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.01960","created_at":"2026-07-05T09:56:59.496161+00:00"},{"alias_kind":"pith_short_12","alias_value":"QVPHHL5TVH4X","created_at":"2026-07-05T09:56:59.496161+00:00"},{"alias_kind":"pith_short_16","alias_value":"QVPHHL5TVH4XP2Q5","created_at":"2026-07-05T09:56:59.496161+00:00"},{"alias_kind":"pith_short_8","alias_value":"QVPHHL5T","created_at":"2026-07-05T09:56:59.496161+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY","json":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY.json","graph_json":"https://pith.science/api/pith-number/QVPHHL5TVH4XP2Q57WIVLAG4TY/graph.json","events_json":"https://pith.science/api/pith-number/QVPHHL5TVH4XP2Q57WIVLAG4TY/events.json","paper":"https://pith.science/paper/QVPHHL5T"},"agent_actions":{"view_html":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY","download_json":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY.json","view_paper":"https://pith.science/paper/QVPHHL5T","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.01960&json=true","fetch_graph":"https://pith.science/api/pith-number/QVPHHL5TVH4XP2Q57WIVLAG4TY/graph.json","fetch_events":"https://pith.science/api/pith-number/QVPHHL5TVH4XP2Q57WIVLAG4TY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY/action/storage_attestation","attest_author":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY/action/author_attestation","sign_citation":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY/action/citation_signature","submit_replication":"https://pith.science/pith/QVPHHL5TVH4XP2Q57WIVLAG4TY/action/replication_record"}},"created_at":"2026-07-05T09:56:59.496161+00:00","updated_at":"2026-07-05T09:56:59.496161+00:00"}