Evidence map›Paper›PMID 36195992›Full record

ArticleChinese medical journal2022

SARS-CoV-2: Has artificial intelligence stood the test of time.

Mir Ibrahim Sajid, Shaheer Ahmed, Usama Waqar, Javeria Tariq, Mohsin Chundrigarh, Samira Shabbir Balouch, Sajid Abaidullah

Abstract read
In one paragraph

Article in Chinese medical journal, 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. Review
  2. [DeepSeek perspective on managing Kawasaki disease in Chinese children].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025
    Article
  3. Article
  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

7 authors.

Mir Ibrahim SajidMedical College, Aga Khan University, Stadium Road, Karachi, Pakistan.
Shaheer AhmedMedlcal College, Islamabad Medical and Dental College, Main Murree Road, Islamabad, Pakistan.
Usama WaqarMedical College, Aga Khan University, Stadium Road, Karachi, Pakistan.
Javeria TariqMedical College, Aga Khan University, Stadium Road, Karachi, Pakistan.
Mohsin ChundrigarhMedical College, Aga Khan University, Stadium Road, Karachi, Pakistan.
Samira Shabbir BalouchOral and Maxillofacial Surgery, King Edward Medical University, Neela Gumbad, Lahore, Pakistan.
Sajid AbaidullahKing Edward Medical University, Neela Gumbad, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractArtificial intelligence (AI) has proven time and time again to be a game-changer innovation in every walk of life, including medicine. Introduced by Dr. Gunn in 1976 to accurately diagnose acute abdominal pain and list potential differentials, AI has since come a long way. In particular, AI has been aiding in radiological diagnoses with good sensitivity and specificity by using machine learning algorithms. With the coronavirus disease 2019 pandemic, AI has proven to be more than just a tool to facilitate healthcare workers in decision making and limiting physician-patient contact during the pandemic. It has guided governments and key policymakers in formulating and implementing laws, such as lockdowns and travel restrictions, to curb the spread of this viral disease. This has been made possible by the use of social media to map severe acute respiratory syndrome coronavirus 2 hotspots, laying the basis of the "smart lockdown" strategy that has been adopted globally. However, these benefits might be accompanied with concerns regarding privacy and unconsented surveillance, necessitating authorities to develop sincere and ethical government-public relations.

Indexed as

COVID-19SARS-CoV-2Artificial IntelligenceCommunicable Disease ControlHumansPandemics

Identifiers

PMID36195992
PMCPMC9521771

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.