International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI Tools in Nursing: A Systematic Review and Meta-Analysis

Author(s) Mrs. Pratibha Thakur, Dr. Somendra Singh Kashyap
Country India
Abstract The integration of Artificial Intelligence (AI) tools into nursing research and practice has the potential to transform healthcare delivery by improving clinical decision-making, enhancing patient outcomes, and optimizing healthcare workflows. This systematic review and meta-analysis aim to evaluate the current state of AI applications in nursing, summarizing the effectiveness, challenges, and opportunities presented by these technologies. A comprehensive search of peer-reviewed literature was conducted, including randomized controlled trials, observational studies, and qualitative research published between 2010 and 2024. Key findings reveal that AI tools, particularly in predictive analytics, diagnostic assistance, and patient monitoring, have shown positive effects on reducing clinical errors, enhancing patient care, and supporting evidence-based practice. However, the integration of AI in nursing faces significant barriers, including concerns regarding data privacy, trust in technology, and the need for continuous education and training for healthcare professionals. This review highlights the critical need for further research to address these challenges, establish clear ethical guidelines, and optimize the adoption of AI tools in nursing. The findings indicate that, when properly integrated, AI can augment nursing practice, improve care efficiency, and contribute to better health outcomes.
Keywords Artificial intelligence (AI), Nursing Research, Nursing Practice, Artificial Intelligence (AI), Patient Outcomes, Clinical Decision-Making.
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-13
Cite This AI Tools in Nursing: A Systematic Review and Meta-Analysis - Mrs. Pratibha Thakur, Dr. Somendra Singh Kashyap - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.36914
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.36914
Short DOI https://doi.org/g84xhj
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