Evidence map›Paper›PMID 38661528›Full record

ArticleJournal of endourology2024

Automated Upper Tract Urothelial Carcinoma Tumor Segmentation During Ureteroscopy Using Computer Vision Techniques.

Daiwei Lu, Amy Reed, Natalie Pace, Amy N Luckenbaugh, Maximilian Pallauf, Nirmish Singla, Ipek Oguz, Nicholas Kavoussi

Open access · goldAbstract read
In one paragraph

Article in Journal of endourology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Artificial intelligence in urology training Enhancing annotation, feedback, and evaluation in robotic, laparoscopic, and endoscopic surgery.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2026
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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

8 authors at 3 institutions in 2 countries.

Daiwei LuDepartment of Computer Science, Vanderbilt University School of Engineering, Nashville, Tennessee, USA.
Amy ReedDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Natalie PaceDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Amy N LuckenbaughDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Maximilian PallaufDepartment of Urology, Johns Hopkins University, Baltimore, Maryland, USA.
Nirmish SinglaDepartment of Urology, Johns Hopkins University, Baltimore, Maryland, USA.
Ipek OguzDepartment of Computer Science, Vanderbilt University School of Engineering, Nashville, Tennessee, USA.
Nicholas KavoussiDepartment of Urology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Vanderbilt University Medical Center · USJohns Hopkins University · USVanderbilt University · US

Funding

A Navigational System for Endoscopic Kidney Stone SurgeryR21DK133742 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KAVOUSSI, NICHOLAS L, OGUZ, IPEK · 2023 to 2024
$452k
NIDDK NIH HHS R21 DK133742
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

UreteroscopyCarcinoma, Transitional CellHumansImage Processing, Computer-AssistedKidney NeoplasmsUreteral NeoplasmsVideo Recordingartificial intelligencecomputer visionendoscopyupper tract urothelial carcinomaureteroscopy

Identifiers

PMID38661528
PMCPMC11947648
OpenAlexW4395465762

What OpenQuestion holds

Textmetadata
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.