Evidence map›Paper›PMID 41959651›Full record

ArticleProceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence2026

Zhengbo Zhou, Dooman Arefan, Margarita Zuley, Shandong Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhengbo ZhouIntelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.
Dooman ArefanDepartment of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.
Margarita ZuleyDepartment of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.
Shandong WuIntelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.

Funding

Ethically-focused multimodal AI models for precision treatments of breast cancerOT2OD037972 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Shandong Wu · 2025 to 2026
$3.7M
SCH: Leverage clinical knowledge to augment deep learning analysis of breast imagesR01EB032896 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WU, SHANDONG · 2021 to 2024
$1.4M
NIBIB NIH HHS R01 EB032896NIH HHS OT2 OD037972
6 · The paper itself

Abstract

Longitudinal analysis of sequential radiological images is hampered by a fundamental data challenge: how to effectively model a sequence of high-resolution images captured at irregular time intervals. This data structure contains indispensable spatial and temporal cues that current methods fail to fully exploit. Models often compromise by either collapsing spatial information into vectors or applying spatio-temporal models that are computationally inefficient and incompatible with non-uniform time steps. We address this challenge with Time-Aware

Identifiers

PMID41959651
PMCPMC13061374

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.