Evidence map›Paper›PMID 36311999›Full record

ReviewWorld journal of diabetes2022

Everything real about unreal artificial intelligence in diabetic retinopathy and in ocular pathologies.

Arvind Kumar Morya, Siddharam S Janti, Priya Sisodiya, Antervedi Tejaswini, Rajendra Prasad, Kalpana R Mali, Bharat Gurnani

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of diabetes, 2022. 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. Article
  2. Review
  3. Review
  4. Review
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

7 authors.

Arvind Kumar MoryaDepartment of Ophthalmology, All India Institute of Medical Sciences Bibinagar, Hyderabad 508126, Telangana, India. bulbul.morya@gmail.com.
Siddharam S JantiDepartment of Ophthalmology, All India Institute of Medical Sciences Bibinagar, Hyderabad 508126, Telangana, India.
Priya SisodiyaDepartment of Ophthalmology, Sadguru Netra Chikitsalaya, Chitrakoot 485001, Madhya Pradesh, India.
Antervedi TejaswiniDepartment of Ophthalmology, All India Institute of Medical Sciences Bibinagar, Hyderabad 508126, Telangana, India.
Rajendra PrasadDepartment of Ophthalmology, R P Eye Institute, New Delhi 110001, New Delhi, India.
Kalpana R MaliDepartment of Pharmacology, All India Institute of Medical Sciences, Bibinagar, Hyderabad 508126, Telangana, India.
Bharat GurnaniDepartment of Ophthalmology, Aravind Eye Hospital and Post Graduate Institute of Ophthalmology, Pondicherry 605007, Pondicherry, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial Intelligence is a multidisciplinary field with the aim of building platforms that can make machines act, perceive, reason intelligently and whose goal is to automate activities that presently require human intelligence. From the cornea to the retina, artificial intelligence (AI) is expected to help ophthalmologists diagnose and treat ocular diseases. In ophthalmology, computerized analytics are being viewed as efficient and more objective ways to interpret the series of images and come to a conclusion. AI can be used to diagnose and grade diabetic retinopathy, glaucoma, age-related macular degeneration, cataracts, IOL power calculation, retinopathy of prematurity and keratoconus. This review article intends to discuss various aspects of artificial intelligence in ophthalmology.

Indexed as

Artificial intelligenceDeep learningDiabetic retinopathyMachine learningOphthalmology

Identifiers

PMID36311999
PMCPMC9606792

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.