Evidence map›Paper›PMID 34359297›Full record

ArticleDiagnostics (Basel, Switzerland)2021

Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on "Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model.

Francesco Gentile, Matteo Ferro, Bartolomeo Della Ventura, Evelina La Civita, Antonietta Liotti, Michele Cennamo, Dario Bruzzese, Raffaele Velotta, Daniela Terracciano

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
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

9 authors at 3 institutions in 1 country.

Francesco GentileDepartment of Experimental and Clinical Medicine, University Magna Graecia of Catanzaro, 88100 Catanzaro, Italy.ORCID 0000-0002-1724-6301
Matteo FerroDivision of Urology, European Institute of Oncology (IEO), IRCCS, Via Ripamonti 435, 20141 Milan, Italy.ORCID 0000-0002-9250-7858
Bartolomeo Della VenturaDepartment of Physics "Ettore Pancini", University of Naples "Federico II", Via Cintia 26 Ed. G, 80126 Naples, Italy.ORCID 0000-0003-2920-6187
Evelina La CivitaDepartment of Translational Medical Sciences, University of Naples "Federico II", 80131 Naples, Italy.
Antonietta LiottiDepartment of Translational Medical Sciences, University of Naples "Federico II", 80131 Naples, Italy.
Michele CennamoDepartment of Translational Medical Sciences, University of Naples "Federico II", 80131 Naples, Italy.
Dario BruzzeseDepartment of Public Health, University of Naples "Federico II", 80131 Naples, Italy.ORCID 0000-0001-9911-4646
Raffaele VelottaDepartment of Physics "Ettore Pancini", University of Naples "Federico II", Via Cintia 26 Ed. G, 80126 Naples, Italy.ORCID 0000-0003-1077-8353
Daniela TerraccianoDepartment of Translational Medical Sciences, University of Naples "Federico II", 80131 Naples, Italy.ORCID 0000-0003-4296-429X
University of Naples Federico II · ITMagna Graecia University · ITRipamonti · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In their comment "Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer [...].

Identifiers

PMID34359297
PMCPMC8307083
OpenAlexW3179446117

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.