Opinion Article - Journal of Clinical Pathology and Laboratory Medicine (2021) Volume 3, Issue 5
Application scenarios for artificial intelligence in nursing care: Rapid review
- Corresponding Author:
- Kathrin Seibert
Department of Institute of Public Health and Nursing Research, High Profile Area Health Sciences, University of Bremen, Bremen, Germany.
E-mail: [email protected]
Artificial intelligence (AI) holds the pledge of supporting nursers’clinical decision- making in complex care situations or conducting tasks that are remote from direct case commerce, similar as attestation processes. There has been an increase in the exploration and development of AI operations for nursing care, but there's a patient lack of an expansive overview covering the substantiation base for promising operation scripts. This study synthesizes literature on operation scripts for AI in nursing care settings as well as highlights conterminous aspects in the ethical, legal, and social converse girding the operation of AI in nursing care . Following a rapid-fire review design, PubMed, CINAHL, Association for Computing machinery digital library, institute of electrical and electronics engineers xplore, digital bibliography and library project, and association for information systems library, as well as the libraries of leading AI conferences, were searched in June 2020. Publications of original quantitative and qualitative exploration, methodical reviews, discussion papers, and essays on the ethical, legal, and social counteraccusations published in English were included. Eligible studies were anatomized on the base of destined selection criteria .
The titles and objectifications of 7016 publications and 704 full textbooks were screened, and 292 publications were included. Hospitals were the most prominent study setting, followed by independent living at home; smaller operation scripts were linked for nursing homes or home care. Utmost studies used machine literacy algorithms, whereas expert or mongrel systems were included in lower than every 10th publication. The operation environment of fastening on image and signal processing with shadowing, monitoring, or the bracket of exertion and health followed by care collaboration and communication, as well as fall discovery, was the main purpose of AI operations. Many studies have reported the goods of AI operations on clinical or organizational issues, lacking particularly in data gathered outside laboratory conditions. In addition to technological conditions, the reporting and addition of certain conditions capture further overarching motifs, similar as data sequestration, safety, and technology acceptance. Ethical, legal, and social counteraccusations reflect the converse on technology use in health care but have substantially not been bandied in meaningful and potentially encompassing detail . The results punctuate the eventuality for the operation of AI systems in different nursing care settings. Considering the lack of findings on the effectiveness and operation of AI systems in real- world scripts, unborn exploration should reflect on a further nursing care – specific perspective toward objects, issues, and benefits. We identify that, crucially, advancement in technological-societal converse that surrounds the ethical and legal counteraccusations of AI operations in nursing care is a necessary coming step .
Clinical Artificial Intelligence
Farther, we outline the need for lesser participation among all of the stakeholders involved. Despite a swell in funded exploration in the operation of digital technologies toward a advanced assurance of quality nursing care, in times of growing societies and skill dearths, the operation of Artificial Intelligence (AI) in nursing practice is still scarce. In this environment, AI can be defined as algorithms that enable learning from data sets to achieve intelligent, thing- acquainted action. Recent methodical and scoping reviews on the operation of AI in nursing exploration (as well as in practice and arising trends), covering original exploration published until October 2019, linked papers listed in medical and multidisciplinary databases. These included studies concentrated on Machine Learning (ML) styles, similar as deep literacy, or on health technologies that incorporate AI approaches themselves, similar as robots or clinical decision support systems. Colorful operation scripts have been linked, including clinical or organizational issues (eg, falls), admission opinions in exigency drug, high- description image recognition, as well as socially assistive robots or health care adjunct chatbots. In addition, recent times have seen an increase in exploration pressing possibilities for the unborn development of AI in nursing care while emphasizing the significance of cooperative, interdisciplinary exploration, and representative, robust data sets .