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pith:542ZKGNW

pith:2026:542ZKGNWEF67DDTIUIW6AV3ZKM
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Capture Timing-Attention of Events in Clinical Time Series

Jia Li, Rui Zhang, Yu Hou

LITT aligns clinical events on a virtual relative timeline to focus attention on their timing for personalized predictions.

arxiv:2602.10385 v4 · 2026-02-11 · cs.LG · cs.AI

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\usepackage{pith}
\pithnumber{542ZKGNWEF67DDTIUIW6AV3ZKM}

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Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
Portable graph bundle live · download bundle · merged state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

LITT enables temporary alignment of sequential events on a virtual relative timeline, thereby enabling event-timing-focused attention and personalized interpretations of clinical trajectories, validated on real-world longitudinal EHR data from 3,276 breast cancer patients to predict the onset timing of cardiotoxicity-induced heart disease.

C2weakest assumption

That treating timing as a computable dimension via relative timestamps on a virtual timeline captures meaningful alignments and causal patterns without introducing artifacts or losing information from the original observed times.

C3one line summary

LITT aligns individual clinical event sequences on a relative timeline to enable timing-aware attention and better prediction of personalized health trajectories.

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-28T02:04:46.132164Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

ef359519b6217df18e68a22de057795324d3ce2268f80f9eb2f31b5be768156b

Aliases

arxiv: 2602.10385 · arxiv_version: 2602.10385v4 · doi: 10.48550/arxiv.2602.10385 · pith_short_12: 542ZKGNWEF67 · pith_short_16: 542ZKGNWEF67DDTI · pith_short_8: 542ZKGNW
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/542ZKGNWEF67DDTIUIW6AV3ZKM \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ef359519b6217df18e68a22de057795324d3ce2268f80f9eb2f31b5be768156b
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "1d0d9069103bfe120ac6aca14ea0c1a666ad3c1816e0a3d69e4f50cf008878ec",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-02-11T00:13:08Z",
    "title_canon_sha256": "598b946c6e9980f642d9eb593146c8a80ba583f0cf998cfcf7259ff8c59b719e"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.10385",
    "kind": "arxiv",
    "version": 4
  }
}