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[Application of Artificial Intelligence Models in Nursing Research].

Cheng-Pei Lin1, Lu-Yen Anny Chen2

  • 1PhD, RN, Assistant Professor, Institute of Community Health Care, National Yang Ming Chiao Tung University, Taiwan, ROC.

Hu Li Za Zhi the Journal of Nursing
|October 1, 2024
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Summary

Artificial intelligence (AI) and machine learning (ML) offer significant potential for advancing nursing research and clinical care. This paper explores ML applications, models, and challenges, advocating for interdisciplinary collaboration to enhance AI integration in nursing.

Keywords:
artificial intelligencemachine learningnursing researchprecision care

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Area of Science:

  • Nursing
  • Computer Science
  • Artificial Intelligence

Context:

  • Rapid advancements in artificial intelligence (AI) are transforming healthcare.
  • Machine learning (ML), a subset of AI, shows promise for nursing research and clinical applications.
  • Current ML integration in nursing is limited but expanding.

Purpose:

  • To introduce machine learning (ML) concepts and models relevant to nursing.
  • To compare ML with traditional statistical methods in healthcare research.
  • To discuss the potential limitations and challenges of ML in nursing.

Summary:

  • The paper details ML types, classifications, and neural network models (RNNs, Transformers, NLP).
  • It explores ML principles, steps, quality monitoring, and compares them to traditional statistical methods.
  • Authors highlight limitations and challenges, emphasizing the need for interdisciplinary collaboration.

Impact:

  • Facilitates understanding of ML for nursing professionals and researchers.
  • Encourages interdisciplinary collaboration between IT and nursing for AI innovation.
  • Aims to maximize AI's potential to drive progress in nursing research and practice.