Evidence map›Paper›PMID 33401373›Full record

ReviewInternational journal of environmental research and public health2021

Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges.

DonHee Lee, Seong No Yoon

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 215 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
215citing papers in PubMed, 13 pooled it
40.4field-weighted citation impact, top 1% of its field
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

215 citing papers in PubMed, 13 syntheses or guidelines pooled it, 938 citations in OpenAlex.

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  3. Artificial intelligence in rehabilitation: a living systematic mapping review - first release.European journal of physical and rehabilitation medicine · 2025
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155 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 2 countries.

DonHee LeeCollege of Business Administration, Inha University, Incheon 22212, Korea.ORCID 0000-0003-2799-8547
Seong No YoonDepartment of Business Edward Waters College, Jacksonville, FL 32209, USA.
Edward Waters University · USInha University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines the current state of artificial intelligence (AI)-based technology applications and their impact on the healthcare industry. In addition to a thorough review of the literature, this study analyzed several real-world examples of AI applications in healthcare. The results indicate that major hospitals are, at present, using AI-enabled systems to augment medical staff in patient diagnosis and treatment activities for a wide range of diseases. In addition, AI systems are making an impact on improving the efficiency of nursing and managerial activities of hospitals. While AI is being embraced positively by healthcare providers, its applications provide both the utopian perspective (new opportunities) and the dystopian view (challenges to overcome). We discuss the details of those opportunities and challenges to provide a balanced view of the value of AI applications in healthcare. It is clear that rapid advances of AI and related technologies will help care providers create new value for their patients and improve the efficiency of their operational processes. Nevertheless, effective applications of AI will require effective planning and strategies to transform the entire care service and operations to reap the benefits of what technologies offer.

Indexed as

Artificial IntelligenceBiomedical TechnologyHealth Care SectorHumansAI-based technologyhealthcare industryopportunities and challengespolicy and management supportreal-world cases

Identifiers

PMID33401373
PMCPMC7795119
OpenAlexW3113541070

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.