Evidence map›Paper›PMID 38929607›Full record

ReviewMedicina (Kaunas, Lithuania)2024

Deep Learning in Neovascular Age-Related Macular Degeneration.

Enrico Borrelli, Sonia Serafino, Federico Ricardi, Andrea Coletto, Giovanni Neri, Chiara Olivieri, Lorena Ulla, Claudio Foti, Paola Marolo, Mario Damiano Toro and 2 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Medicina (Kaunas, Lithuania), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

12 authors.

Enrico BorrelliDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.ORCID 0000-0003-2815-5031
Sonia SerafinoDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.
Federico RicardiDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.
Andrea ColettoDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.ORCID 0009-0000-2800-0019
Giovanni NeriDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.ORCID 0009-0008-7176-9593
Chiara OlivieriDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.ORCID 0009-0002-5207-264X
Lorena UllaDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.
Claudio FotiDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.
Paola MaroloDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.ORCID 0000-0002-8881-0926
Mario Damiano ToroEye Clinic, Public Health Department, University of Naples Federico II, 80138 Naples, Italy.ORCID 0000-0001-7152-2613
Francesco BandelloDepartment of Ophthalmology, Vita-Salute San Raffaele University, 20132 Milan, Italy.ORCID 0000-0003-3238-9682
Michele ReibaldiDivision of Ophthalmology, Department of Surgical Sciences, University of Turin, Via Verdi, 8, 10124 Turin, Italy.ORCID 0000-0003-1368-6729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Deep LearningMacular DegenerationTomography, Optical CoherenceHumansage-related macular degenerationartificial intelligencebiomarkerdeep learningneovascular age-related macular degenerationneovascularizationoptical coherence tomography

Identifiers

PMID38929607
PMCPMC11205843

What OpenQuestion holds

Textmetadata
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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.