Evidence map›Paper›PMID 38264676›Full record

ArticleClinical pathology (Thousand Oaks, Ventura County, Calif.)

Impact of Artificial Intelligence (AI) Technology in Healthcare Sector: A Critical Evaluation of Both Sides of the Coin.

Md Ashrafur Rahman, Evangelos Victoros, Julianne Ernest, Rob Davis, Yeasna Shanjana, Md Rabiul Islam

Abstract read
In one paragraph

Article in Clinical pathology (Thousand Oaks, Ventura County, Calif.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  9. Article
  10. Artificial intelligence -assisted tinnitus support with ChatGPT-4.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Article
  11. Article
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  14. Article
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  18. Evaluating privacy policies of AI-powered mHealth iOS applications.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  19. Integrating enterprise risk management to address AI-related risks in healthcare: Strategies for effective risk mitigation and implementation.Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management · 2025
    Article
  20. 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

6 authors.

Md Ashrafur RahmanNesbitt School of Pharmacy Wilkes University, Wilkes-Barre, PA, USA.
Evangelos VictorosNesbitt School of Pharmacy Wilkes University, Wilkes-Barre, PA, USA.
Julianne ErnestNesbitt School of Pharmacy Wilkes University, Wilkes-Barre, PA, USA.
Rob DavisNesbitt School of Pharmacy Wilkes University, Wilkes-Barre, PA, USA.
Yeasna ShanjanaDepartment of Environmental Sciences, North South University, Bashundhara, Dhaka, Bangladesh.
Md Rabiul IslamSchool of Pharmacy, BRAC University, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The influence of artificial intelligence (AI) has drastically risen in recent years, especially in the field of medicine. Its influence has spread so greatly that it is determined to become a pillar in the future medical world. A comprehensive literature search related to AI in healthcare was performed in the PubMed database and retrieved the relevant information from suitable ones. AI excels in aspects such as rapid adaptation, high diagnostic accuracy, and data management that can help improve workforce productivity. With this potential in sight, the FDA has continuously approved more machine learning (ML) software to be used by medical workers and scientists. However, there are few controversies such as increased chances of data breaches, concern for clinical implementation, and potential healthcare dilemmas. In this article, the positive and negative aspects of AI implementation in healthcare are discussed, as well as recommended some potential solutions to the potential issues at hand.

Indexed as

Artificial intelligencedrug designhealthcarehealth servicesmachine learningpublic health

Identifiers

PMID38264676
PMCPMC10804900

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.