Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

Buchanan, Christine; Howitt, M Lyndsay; Wilson, Rita; Booth, Richard; Risling, Tracie; Bamford, Megan

doi:10.2196/23939

Cited by 87 publications

(104 citation statements)

References 123 publications

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“…Recent systematic and scoping reviews on the application of AI in nursing research (as well as in practice and emerging trends), covering original research published until October 2019, identified papers listed in medical and multidisciplinary databases. These included studies focused on machine learning (ML) methods, such as deep learning [ 2 ], or on health technologies that incorporate AI approaches themselves, such as robots or clinical decision support systems [ 3 ]. Various application scenarios have been identified, including clinical or organizational outcomes (eg, falls), admission decisions in emergency medicine, high-definition image recognition, as well as socially assistive robots or health care assistant chatbots [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

et al. 2021

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Background Artificial intelligence (AI) holds the promise of supporting nurses’ clinical decision-making in complex care situations or conducting tasks that are remote from direct patient interaction, such as documentation processes. There has been an increase in the research and development of AI applications for nursing care, but there is a persistent lack of an extensive overview covering the evidence base for promising application scenarios. Objective This study synthesizes literature on application scenarios for AI in nursing care settings as well as highlights adjacent aspects in the ethical, legal, and social discourse surrounding the application of AI in nursing care. Methods Following a rapid review design, PubMed, CINAHL, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers Xplore, Digital Bibliography & 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 research, systematic reviews, discussion papers, and essays on the ethical, legal, and social implications published in English were included. Eligible studies were analyzed on the basis of predetermined selection criteria. Results The titles and abstracts of 7016 publications and 704 full texts were screened, and 292 publications were included. Hospitals were the most prominent study setting, followed by independent living at home; fewer application scenarios were identified for nursing homes or home care. Most studies used machine learning algorithms, whereas expert or hybrid systems were entailed in less than every 10th publication. The application context of focusing on image and signal processing with tracking, monitoring, or the classification of activity and health followed by care coordination and communication, as well as fall detection, was the main purpose of AI applications. Few studies have reported the effects of AI applications on clinical or organizational outcomes, lacking particularly in data gathered outside laboratory conditions. In addition to technological requirements, the reporting and inclusion of certain requirements capture more overarching topics, such as data privacy, safety, and technology acceptance. Ethical, legal, and social implications reflect the discourse on technology use in health care but have mostly not been discussed in meaningful and potentially encompassing detail. Conclusions The results highlight the potential for the application of AI systems in different nursing care settings. Considering the lack of findings on the effectiveness and application of AI systems in real-world scenarios, future research should reflect on a more nursing care–specific perspective toward objectives, outcomes, and benefits. We identify that, crucially, an advancement in technological-societal discourse that surrounds the ethical and legal implications of AI applications in nursing care is a necessary next step. Further, we outline the need for greater participation among all of the stakeholders involved.

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Section: Introductionmentioning

confidence: 99%

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

et al. 2021

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“…Although many of the purported potential benefits of AI (eg, improved patient outcomes, streamlined workflow, improved efficiency) have yet to be fully shown in nursing research, 6 it is inevitable that AI technologies will be used more regularly to support and extend nurses' cognitive, decision making, and potentially labor functions. 15 These opportunities bring new and dynamic practice considerations for nursing and interprofessional expertise.…”

Section: Investigate Artificial Intelligence In Nursing Practicementioning

confidence: 99%

“…The development and application to nursing of systems based on AI are still in their infancy. But preliminary evidence suggests virtual chatbots could play a part in streamlining communication with patients, and robots could increase the emotional and social support patients receive from nurses, while acknowledging inherent challenges such as data privacy, ethics, and cost effectiveness 6…”

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confidence: 99%

How the nursing profession should adapt for a digital future

Booth

Strudwick

McBride

et al. 2021

BMJ

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115

105

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“…These AI and ML technologies require to instruct patients to ensure that patient does not mistake intelligent system for a human-driven application. Furthermore, consent of applications obtained outside the medical environment rises thorny concerns [ 68 ]. AI is susceptible to misjudgment and incorrect risks.…”

Section: Ethical Concern Of Artificial Intelligence and Machine Learning Based Robotic Therapymentioning

confidence: 99%

Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

Iqbal¹,

et al. 2021

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Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.

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Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

Cited by 87 publications

References 123 publications

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

How the nursing profession should adapt for a digital future

Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

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