scholarly journals Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence

Author(s):  
Hanna Von Gerich ◽  
Hans Moen ◽  
Lorraine J. Block ◽  
Charlene H. Chu ◽  
Haley DeForest ◽  
...  
2020 ◽  
Author(s):  
Avishek Choudhury

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.


2021 ◽  
Vol 11 (2) ◽  
pp. 870
Author(s):  
Galena Pisoni ◽  
Natalia Díaz-Rodríguez ◽  
Hannie Gijlers ◽  
Linda Tonolli

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed.


Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1317
Author(s):  
Maria Elena Laino ◽  
Angela Ammirabile ◽  
Alessandro Posa ◽  
Pierandrea Cancian ◽  
Sherif Shalaby ◽  
...  

Diagnostic imaging is regarded as fundamental in the clinical work-up of patients with a suspected or confirmed COVID-19 infection. Recent progress has been made in diagnostic imaging with the integration of artificial intelligence (AI) and machine learning (ML) algorisms leading to an increase in the accuracy of exam interpretation and to the extraction of prognostic information useful in the decision-making process. Considering the ever expanding imaging data generated amid this pandemic, COVID-19 has catalyzed the rapid expansion in the application of AI to combat disease. In this context, many recent studies have explored the role of AI in each of the presumed applications for COVID-19 infection chest imaging, suggesting that implementing AI applications for chest imaging can be a great asset for fast and precise disease screening, identification and characterization. However, various biases should be overcome in the development of further ML-based algorithms to give them sufficient robustness and reproducibility for their integration into clinical practice. As a result, in this literature review, we will focus on the application of AI in chest imaging, in particular, deep learning, radiomics and advanced imaging as quantitative CT.


Heliyon ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e06626
Author(s):  
Paulina Cecula ◽  
Jiakun Yu ◽  
Fatema Mustansir Dawoodbhoy ◽  
Jack Delaney ◽  
Joseph Tan ◽  
...  

2019 ◽  
Vol 36 (4) ◽  
pp. 101392 ◽  
Author(s):  
Weslei Gomes de Sousa ◽  
Elis Regina Pereira de Melo ◽  
Paulo Henrique De Souza Bermejo ◽  
Rafael Araújo Sousa Farias ◽  
Adalmir Oliveira Gomes

Author(s):  
Alexandra Cernat ◽  
Robin Z. Hayeems ◽  
Wendy J. Ungar

AbstractCascade genetic testing is the identification of individuals at risk for a hereditary condition by genetic testing in relatives of people known to possess particular genetic variants. Cascade testing has health system implications, however cascade costs and health effects are not considered in health technology assessments (HTAs) that focus on costs and health consequences in individual patients. Cascade health service use must be better understood to be incorporated in HTA of emerging genetic tests for children. The purpose of this review was to characterise published research related to patterns and costs of cascade health service use by relatives of children with any condition diagnosed through genetic testing. To this end, a scoping literature review was conducted. Citation databases were searched for English-language papers reporting uptake, costs, downstream health service use, or cost-effectiveness of cascade investigations of relatives of children who receive a genetic diagnosis. Included publications were critically appraised, and findings were synthesised. Twenty publications were included. Sixteen had a paediatric proband population; four had a combined paediatric and adult proband population. Uptake of cascade testing varied across diseases, from 37% for cystic fibrosis, 39% to 65% for hypertrophic cardiomyopathy, and 90% for rare monogenic conditions. Two studies evaluated costs. It was concluded that cascade testing in the child-to-parent direction has been reported in a variety of diseases, and that understanding the scope of cascade testing will aid in the design and conduct of HTA of emerging genetic technologies to better inform funding and policy decisions.


2021 ◽  
Vol 13 (10) ◽  
pp. 408-413
Author(s):  
Anna Somers

Paramedics often come across death because of the nature of their work. Attending an incident involving the death of a patient could affect a paramedic's mental health. A scoping literature review surrounding the readiness and education regarding death in the prehospital setting for paramedic students was carried out. Given the potential impact upon practitioner mental health, the review aimed to determine the quality and extent of new research regarding education in death for paramedics. Four themes arose from the review: inadequate preparation; methods of death education; improved confidence; and implications for more research.


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