Evidence map›Paper›PMID 37952245›Full record

ReviewIrish journal of medical science2024

Artificial intelligence in medical science: a review.

Simrata Bindra, Richa Jain

Abstract readReview
PubMed Publisher
In one paragraph

Review in Irish journal of medical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 pooled it
–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

27 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  15. Facilitators and barriers for using artificial intelligence in cancer pain assessment: a qualitative study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
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  16. Article
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  19. Artificial Intelligence in Medical Care - Patients' Perceptions on Caregiving Relationships and Ethics: A Qualitative Study.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
  20. 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

2 authors.

Simrata BindraDepartment of Physics, Motilal Nehru College, Benito Juarez Road, New Delhi, 110021, India.
Richa JainDepartment of Physics, Motilal Nehru College, Benito Juarez Road, New Delhi, 110021, India. richaj80@gmail.com.ORCID http://orcid.org/0000-0001-6199-3542

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is a technique to make intelligent machines, mainly by using smart computer programs. It is based on a statistical analysis of data or machine learning. Using machine learning, software algorithms are designed according to the desired application. These techniques are found to have the potential for advancement in the medical field by generating new and significant perceptions from the data generated using various types of healthcare tests. Artificial intelligence (AI) in medicine is of two types: virtual and physical. The virtual part decides the treatment using electronic health record systems using various sensors whereas the physical part assists robots to perform surgeries, implants, replacement of various organs, elderly care, etc. Using AI, a machine can examine various kinds of health care test reports in one go which could save the time, money, and increase the chances of the patient to be treated without any hassles. At present, artificial intelligence (AI) is used while deciding the treatment, and medications using various tools which could analyze X-rays, CT scans, MRIs, and any other data. During the COVID pandemic, there was a huge/massive demand for AI-supported technologies and many of those were created during that time. This study is focused on various applications of AI in healthcare.

Indexed as

Artificial IntelligenceCOVID-19HumansMachine LearningArtificial intelligence (AI)Clustered regularly interspaced short palindromic repeats (CRISPR)Computer visionDeep learningMachine learningMYCIN

Identifiers

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.