Evidence map›Paper›PMID 32845382›Full record

ReviewDer Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft2020

[Multimodal imaging and evaluation in the age of artificial intelligence].

Olivier Morelle, Maximilian Wintergerst, Robert P Finger

Abstract readReview
PubMed Publisher
In one paragraph

Review in Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. [Artificial intelligence in ophthalmology].Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Olivier MorelleB-IT und Institut für Informatik, Universität Bonn, Bonn, Deutschland.
Maximilian WintergerstAbteilung für Augenheilkunde, Universitätsklinikum Bonn, Ernst-Abbe-Str. 2, 53127, Bonn, Deutschland.
Robert P FingerAbteilung für Augenheilkunde, Universitätsklinikum Bonn, Ernst-Abbe-Str. 2, 53127, Bonn, Deutschland. robert.finger@ukbonn.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multimodal imaging is able to image the retina in unprecedented detail, and the joint analysis (integration) of these data not only enables the securing of diagnoses, but also a more precise definition; however, humans encounter temporal and cognitive limitations in the analysis of this amount of information, so that the potential of a joint examination of the findings is largely unused to date. Automatic image processing and methods, which are summarized under the collective term of artificial intelligence (AI), are able to overcome the bottleneck in the evaluation and to exploit the full potential of the available data. A basic understanding of AI methods and the ability to implement them will become increasingly more important for ophthalmologists in the future. In this article we give an insight into the functionality of AI methods and the current state of research in the field of automatic image analysis.

Indexed as

Artificial IntelligenceDeep LearningForecastingHumansImage Processing, Computer-AssistedMultimodal ImagingAutomatic image analysisAutomatic image processingMachine learningOphthalmologyRetina

Identifiers

PMID32845382

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.