Pith Number

pith:L6REGX6O

pith:2026:L6REGX6O4ODLPL52FD32Y46K4F

not attested not anchored not stored refs resolved

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction

Bin Cui, Erik Cambria, Min Hun Lee, Pujun Feng, Seyed Ehsan Saffari, Siew-Kei Lam, Tao Tan, Tong Yang, Xiaoyu Guo, Xiaoyu Zhang, Xibin Sun, Yangtao Zhou, Yue Sun

A unified framework links patient forecasts, counterfactual treatment paths, and policy checks by jointly modeling disease, treatment choices, and observation biases.

arxiv:2605.16927 v1 · 2026-05-16 · cs.AI

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\usepackage{pith}
\pithnumber{L6REGX6O4ODLPL52FD32Y46K4F}

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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

We present the first unified framework bridging forecasting, counterfactual trajectories, and policy evaluation across discrete/continuous time, explicitly addressing treatment assignment, time-varying confounding, and observation bias.

C2weakest assumption

That the six linked components (three decision tasks and three data-generating mechanisms) are sufficient to determine identifiability and to comprehensively map existing method families without material loss of structure or coverage from prior literature.

C3one line summary

A review proposing a unified framework for intervention-aware disease trajectory modeling in clinical AI, organized around three decision tasks and three data-generating mechanisms.

References

107 extracted · 107 resolved · 3 Pith anchors

[1] An empirical transition matrix for non-homogeneous markov chains based on censored observations.Scandinavian Journal of Statistics, 5(3):141–150, 1978 1978

[2] Analyzing patient trajectories with artificial intelligence.Journal of medical internet research, 23(12):e29812, 2021 2021

[3] Gill, and Niels Keiding.Statistical Models Based on Counting Processes 1993

[4] Joshua D. Angrist, Guido W. Imbens, and Donald B. Rubin. Identification of causal effects using instrumental variables.Journal of the American Statistical Association, 91(434):444–455, 1996 1996

[5] Peter C. Austin, Frank E. Harrell, and Davide van Klaveren. Graphical calibration curves and the integrated calibration index (ICI) for survival models.Statistics in Medicine, 39(21):2714–2742, 2020 2020

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:03:31.166829Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

5fa2435fcee386b7afba28f7ac73cae171cbb6e65ee578aee2f1280ecef5b4ec

Aliases

arxiv: 2605.16927 · arxiv_version: 2605.16927v1 · doi: 10.48550/arxiv.2605.16927 · pith_short_12: L6REGX6O4ODL · pith_short_16: L6REGX6O4ODLPL52 · pith_short_8: L6REGX6O

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/L6REGX6O4ODLPL52FD32Y46K4F \
  | 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: 5fa2435fcee386b7afba28f7ac73cae171cbb6e65ee578aee2f1280ecef5b4ec

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "796d9f781f78a25a7d7cb76532677ab782b85b4bf3666afa32db6cb94412bb19",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-05-16T10:45:26Z",
    "title_canon_sha256": "42c39f5a326249521ac385aee169cd19cab4b3c6468ff4f42a8c0166c4139c25"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16927",
    "kind": "arxiv",
    "version": 1
  }
}