Evidence map›Paper›PMID 36595077›Full record

ArticleWorld journal of urology2023

Computer-aided diagnosis in prostate cancer: a retrospective evaluation of the Watson Elementary

Gianni Vittori, Mara Bacchiani, Antonio Andrea Grosso, Maria Rosaria Raspollini, Neri Giovannozzi, Lorenzo Righi, Fabrizio Di Maida, Simone Agostini, Fausto De Nisco, Andrea Mari and 1 more

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Article in World journal of urology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Gianni VittoriDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Mara BacchianiDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Antonio Andrea GrossoDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Maria Rosaria RaspolliniHistopathology and Molecular Diagnostics, Careggi Hospital, University of Florence, Florence, Italy.
Neri GiovannozziHistopathology and Molecular Diagnostics, Careggi Hospital, University of Florence, Florence, Italy.
Lorenzo RighiClinical Trial Center, Careggi University Hospital, Florence, Italy.
Fabrizio Di MaidaDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Simone AgostiniDepartment of Radiology, Careggi Hospital, University of Florence, Florence, Italy.
Fausto De NiscoDepartment of Radiology, Careggi Hospital, University of Florence, Florence, Italy.
Andrea MariDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy. andrea.mari@unifi.it.ORCID http://orcid.org/0000-0001-9070-5706
Andrea MinerviniDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Azienda Ospedaliero-Universitaria Careggi · ITUniversity of Florence · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeComputer-aided diagnosis (CAD) may improve prostate cancer (PCa) detection and support multiparametric magnetic resonance imaging (mpMRI) readers for better characterization. We evaluated Watson Elementary

methodsPatients treated with RARP between 2020 and 2021 were selected. WE

resultsOverall, tumor presence was confirmed in 46 (92%) WE

conclusionThe WE

Indexed as

Prostatic NeoplasmsRoboticsComputersHumansMagnetic Resonance ImagingMaleProstateProstatectomyRetrospective StudiesArtificial intelligenceIndex lesionMagnetic resonance imagingProstate cancer

Identifiers

PMID36595077
OpenAlexW4313453319

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.