Pith Number

pith:PDHGYEHQ

pith:2026:PDHGYEHQNBUTPWSNZRTEXR5CF4

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Time-driven Survival Analysis from FDG-PET/CT in Non-Small Cell Lung Cancer

Ashish Chauhan, Elin Lundstr\"om, H{\aa}kan Ahlstr\"om, Joel Kullberg, Johan \"Ofverstedt, Sambit Tarai, Therese Sj\"oholm, Veronica Sanchez Rodriguez

A model that adds a time-horizon input to FDG-PET/CT image embeddings predicts overall survival more accurately in non-small cell lung cancer.

arxiv:2604.06885 v1 · 2026-04-08 · cs.CV

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\pithnumber{PDHGYEHQNBUTPWSNZRTEXR5CF4}

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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

The incorporation of temporal data with image embeddings demonstrated an advantage in predicting OS, outperforming the baseline method with an improvement in AUC of 4.3%.

C2weakest assumption

That the U-CAN cohort (n=556 training, n=292 test) is representative of broader NSCLC populations and that the time-horizon input generalizes without overfitting to the specific follow-up patterns or censoring mechanisms in this dataset.

C3one line summary

A time-aware ResNet-based model on PET/CT images improves overall survival prediction in NSCLC by incorporating temporal data, achieving 4.3% higher AUC than fixed-time baselines.

References

26 extracted · 26 resolved · 0 Pith anchors

[1] Siegel, Isabelle Soerjomataram, and Ahmedin Jemal 2022 · doi:10.3322/caac.21834

[2] Kolb T, M¨ uller S, M¨ oller P, et al., Molecular heterogeneity in histomorphologic subtypes of lung adenocarcinoma represents a challenge for treatment decision, Neoplasia 49 (2024) 100955.doi:https: 2024 · doi:10.1016/j.neo.2023.100955

[3] Lababede O, Meziane MA, The Eighth Edition of TNM Staging of Lung Cancer: Reference Chart and Diagrams, Oncologist 23 (7) (2018) 844–848.doi:https: //doi.org/10.1634/theoncologist.2017-0659. 15 2018 · doi:10.1634/theoncologist.2017-0659

[4] Alexander M, Wolfe R, Ball D, et al., Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer, Br J Cancer 117 (5) (2017) 744–751.doi:h 2017 · doi:10.1038/bjc.2017.232

[5] Yang CH, Moi SH, Ou-Yang F, et al., Identifying Risk Stratification Associated With a Cancer for Overall Survival by Deep Learning-Based CoxPH, IEEE Access 7 (2019) 67708–67717.doi:https://doi.org/10. 2019 · doi:10.1109/access.2019.2916586

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-25T02:01:19.187692Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

78ce6c10f0686937da4dcc664bc7a22f076cc567706d3176a78d3e2db63c663a

Aliases

arxiv: 2604.06885 · arxiv_version: 2604.06885v1 · doi: 10.48550/arxiv.2604.06885 · pith_short_12: PDHGYEHQNBUT · pith_short_16: PDHGYEHQNBUTPWSN · pith_short_8: PDHGYEHQ

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/PDHGYEHQNBUTPWSNZRTEXR5CF4 \
  | 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: 78ce6c10f0686937da4dcc664bc7a22f076cc567706d3176a78d3e2db63c663a

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "8c7078b26e51ea8ad170419e7e6554e3149e854c9d883e16d99716584d980d83",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-08T09:43:30Z",
    "title_canon_sha256": "51070a5d4e2c2462e6ce43d8a2b9debd9c30158db020777f7985539129fdd18b"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.06885",
    "kind": "arxiv",
    "version": 1
  }
}