Literature DB >> 26021669

Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

Pei-Hung Liao1, Pei-Ti Hsu2, William Chu3, Woei-Chyn Chu4.   

Abstract

This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics.
© The Author(s) 2013.

Entities:  

Keywords:  artificial intelligence technology; decision-making support; nursing informatics

Mesh:

Year:  2015        PMID: 26021669     DOI: 10.1177/1460458213509806

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  7 in total

1.  Application of Machine Learning in Developing Decision-Making Support Models for Decompressed Vertebroplasty.

Authors:  Pei-Hung Liao; Yu-Chuan Tsuei; William Chu
Journal:  Healthcare (Basel)       Date:  2022-01-23

2.  Clinician involvement in research on machine learning-based predictive clinical decision support for the hospital setting: A scoping review.

Authors:  Jessica M Schwartz; Amanda J Moy; Sarah C Rossetti; Noémie Elhadad; Kenrick D Cato
Journal:  J Am Med Inform Assoc       Date:  2021-03-01       Impact factor: 4.497

3.  Dynamic Clinical Algorithms: Digital Technology Can Transform Health Care Decision-Making.

Authors:  David Bell; Noni Gachuhi; Nassim Assefi
Journal:  Am J Trop Med Hyg       Date:  2018-01       Impact factor: 2.345

Review 4.  Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review.

Authors:  Kathrin Seibert; Dominik Domhoff; Dominik Bruch; Matthias Schulte-Althoff; Daniel Fürstenau; Felix Biessmann; Karin Wolf-Ostermann
Journal:  J Med Internet Res       Date:  2021-11-29       Impact factor: 5.428

5.  A cumulative prospect theory-based method for group medical emergency decision-making with interval uncertainty.

Authors:  Jiayi Sun; Xiang Zhou; Juan Zhang; Kemei Xiang; Xiaoxiong Zhang; Ling Li
Journal:  BMC Med Inform Decis Mak       Date:  2022-05-06       Impact factor: 3.298

6.  Nursing in the Age of Artificial Intelligence: Protocol for a Scoping Review.

Authors:  Christine Buchanan; M Lyndsay Howitt; Rita Wilson; Richard G Booth; Tracie Risling; Megan Bamford
Journal:  JMIR Res Protoc       Date:  2020-04-16

Review 7.  Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review.

Authors:  Christine Buchanan; M Lyndsay Howitt; Rita Wilson; Richard G Booth; Tracie Risling; Megan Bamford
Journal:  JMIR Nurs       Date:  2021-01-28
  7 in total

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