Evidence map›Paper›PMID 42337001›Full record

ArticleNPJ digital medicine2026

End to end AI system for surgical gesture sequence recognition and clinical outcome prediction.

Xi Li, Nicholas Matsumoto, Ujjwal Pasupulety, Atharva Deo, Cherine Yang, Jay Moran, Miguel E Hernandez, Peter Wager, Jasmine Lin, Jeanine Kim and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Overcoming Metacognitive Bias: What Surgeons Can Learn From Athletes.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026
    Article
  2. Article
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

14 authors.

Xi LiDepartment of Computational Biomedicine, Center for ArtificialIntelligence Research and Education, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Nicholas MatsumotoDepartment of Computational Biomedicine, Center for ArtificialIntelligence Research and Education, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Ujjwal PasupuletyDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Atharva DeoDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Cherine YangDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Jay MoranDepartment of Computational Biomedicine, Center for ArtificialIntelligence Research and Education, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Miguel E HernandezDepartment of Computational Biomedicine, Center for ArtificialIntelligence Research and Education, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Peter WagerDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Jasmine LinDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Jeanine KimDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA.
Alvin C GohDepartment of Urology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Christian WagnerDepartment of Urology, Pediatric Urology and Urologic Oncology, St.Antonius-Hospital, Gronau, Germany.
Geoffrey A SonnDepartment of Urology, Stanford University Medical Center, Stanford, CA, USA.
Andrew J HungDepartment of Urology, Cedars Sinai Medical Center, Los Angeles, CA, USA. andrew.hung@cshs.org.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Preserving Erectile Function by Quantifying the Nerve-Sparing step of the Robotic ProstatectomyR01CA273031 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Jim Hu, Andrew Hung · 2022 to 2026
$3.6M
NCI NIH HHS P30 CA008748NCI NIH HHS R01CA273031
6 · The paper itself

Abstract

Fine-grained analysis of intraoperative behavior and its impact on patient outcomes remains a longstanding challenge. We present Frame-to-Outcome (F2O), an end-to-end system that translates tissue dissection videos into gesture sequences and uncovers patterns associated with postoperative outcomes. Leveraging transformer-based spatial and temporal modeling and frame-wise classification, F2O robustly detects consecutive short (˜2 s) gestures in the nerve-sparing step of robot-assisted radical prostatectomy (AUC: 0.80 frame-level; 0.81 video-level). F2O-derived features-gesture frequency, duration, and transitions-predicted postoperative outcomes with accuracy comparable to human annotations (0.79 vs. 0.75; overlapping 95% CI). Across 25 shared features, effect size directions were concordant with small differences (∆d

Identifiers

PMID42337001
PMCPMC13319110

What OpenQuestion holds

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LicenceCC BY
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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.