The role of artificial intelligence in healthcare: a structured literature review
The position of synthetic intelligence in healthcare: a structured literature overview
BMC Medical Informatics and Pronouncement Making volume 21,
Article variety: one hundred twenty five (2021) Cite this newsletter
Abstract
Background/Introduction
Artificial intelligence (AI) within the healthcare area is
receiving attention from researchers and health specialists. Few preceding
studies have investigated this subject matter from a multi-disciplinary
perspective, together with accounting, business and management, selection
sciences and health professions.
Methods
The established literature review with its reliable and
replicable studies protocol permitted the researchers to extract 288
peer-reviewed identifications from Scopus. The playwrights used qualitative and
quantitative variables to examine authors, journals, key phrases, and
collaboration networks among researchers. Additionally, the paper advanced from
the Bibliometrix R software program bundle.
Results
The investigation confirmed that the literature on this
discipline is rising. It specializes in health offerings management, predictive
medicinal drug, affected person records and diagnostics, and medical
selection-making. The United States, China, and the United Territory
contributed the highest variety of studies. Keyword analysis discovered that AI
can support physicians in creating a diagnosis, predicting the unfold of
illnesses and customising remedy paths.
Conclusions
The literature famous numerous AI programs for health
offerings and a circulation of studies that has no longer fully been blanketed.
For example, AI initiatives require skills and facts great attention for
statistics-in depth evaluation and information-primarily based management.
Insights can help researchers and fitness professionals understand and cope
with future research on AI in the healthcare discipline.
Background
Artificial intelligence (AI) commonly applies to
computational technologies that emulate mechanisms assisted through human
intelligence, which include thought, deep gaining knowledge of, model,
engagement, and sensory expertise [1, 2]. Some devices can execute a function
that normally includes human interpretation and selection-making [3, 4]. These
techniques have an interdisciplinary method and may be carried out to one of a
kind fields, inclusive of remedy and health. AI has been involved in medication
given that as early as the Nineteen Fifties, when physicians made the first challenges
to improve their diagnoses the usage of laptop-aided applications [5, 6].
Interest and advances in clinical AI programs have surged in latest years
because of the substantially superior computing electricity of modern computer
systems and the sizable amount of virtual statistics to be had for series and
utilisation . AI is step by step converting scientific practice. There are
several AI submissions in medicine that can be used in a ramification of medical
fields, which includes clinical, diagnostic, rehabilitative, surgical, and
predictive practices. Another essential region of drugs where AI is making an
impact is medical choice-making and sickness prognosis. AI technologies can
ingest, examine, and report large volumes of data across specific modalities to
detect disease and manual medical decisions [3, 8]. AI programs can cope with
the huge quantity of information produced in medicinal drug and locate new
facts that might otherwise remain hidden in the mass of clinical huge
information [9,10,11]. These technologies also can perceive new drugs for
health offerings control and patient care treatments [5, 6].
Courage inside the software of AI is seen via a seek in the
number one studies databases. However, as Meskò et al. Discover, the generation
will potentially reduce care expenses and repetitive operations by using
focusing the medical career on crucial thinking and medical creativity. As Cho
et al. In addition Doyle et al. [8, 9] add, the AI attitude is thrilling;
however, new research might be had to set up the efficacy and applications of
AI inside the clinical field .
Our paper may even focus on AI techniques for healthcare
from the accounting, business, and control views. The authors used the based
literature review (SLR) approach for its reliable and replicable research
protocol and decided on bibliometric variables as resources of investigation.
Bibliometric usage allows the recognition of the principle quantitative
variables of the have a look at circulate . This method facilitates the
detection of the required information of a selected research challenge, which
includes field authors, quantity of courses, keywords for interplay between
variables (guidelines, houses and governance) and u . S . A . Records . It also
allows the software of the technology mapping technique . Our paper followed
the Bibliometrix R bundle and the biblioshiny web interface as equipment of
evaluation .
The research offers the following insights for destiny
researchers and practitioners:
bibliometric records on 288 peer-reviewed English papers
from the Scopus collection.
Identification of leading journals on this discipline,
consisting of Journal of Medical Systems, Studies in Health Technology and
Informatics, IEEE Monthly of Biomedical and Health Informatics, and Decision
Support Systems.
Qualitative and quantitative records on authors’ Lotka’s
law, h-index, g-index, m-index, keyword, and citation data.
Research on specific nation state to assess AI in the
shipping and effectiveness of healthcare, quotes, and networks inside each
place.
A subject matter dendrogram take a look at that identifies 5
research clusters: health offerings management, predictive medication, affected
person records, diagnostics, and eventually, clinical selection-making.
An in-depth dialogue that develops theoretical and sensible
implications for future research.
The paper is organised as follows. Section 2 lists the
principle bibliometric articles in this area. Section three elaborates on the
method. Section four presents the findings of the bibliometric analysis.
Section five discusses the principle elements of AI in healthcare based at the
have a look at outcomes. Section 6 concludes the thing with future implications
for studies.
Related works and originality
As advised by means of Zupic and Čater , a research
circulate can be evaluated with bibliometric strategies that can introduce
objectivity and mitigate researcher bias. For this reason, bibliometric
techniques are attracting growing interest amongst researchers as a dependable
and impersonal studies analytical approach [16, 17]. Recently, bibliometrics
has been an important approach for analysing and predicting studies tendencies
. Table 1 lists different research that has used a similar method within the
research movement investigated.
The medical articles suggested display sizeable differences
in keywords and research topics that have been formerly studied. The
bibliometric analysis of Huang et al. Describes rehabilitative medication using
virtual truth era. According to the authors, the number one goal of
rehabilitation is to enhance and restore purposeful capacity and high-quality
of life for patients with physical impairments or disabilities. In latest
years, many healthcare disciplines were privileged to get admission to numerous
technology that provide gear for each research and scientific intervention.