ARTIFICIAL INTELLIGENCE IN NURSING: DRIVING A NEW STANDARD IN PATIENT CARE

In the recent decade, artificial intelligence (AI) has emerged as a transformative force in healthcare, promising to enhance patient outcomes through predictive analytics, personalized care, and streamlined workflows 1,2 .For nursing professionals, integrating AI into clinical practice is not just a technological evolution -it represents an unrealized opportunity to reinforce the human-centric mission of care with powerful data-driven insights 3 .AI should not be viewed as a replacement but rather as a complement to nursing care 4 .Figure 1 illustrates an overview of areas where AI have potential to improve status quo and major challenges with the use and implementation of AI 5 .AI's ability to analyze large datasets and identify patterns has the potential to revolutionize decision-making in clinical care.Predictive analytics can help nurses anticipate complications 6 , such as sepsis 7 , foot ulcers development in diabetes 8 , in-hospital falls injuries 9 , or exacerbation in chronic obstructive pulmonary disease 10,11 , enabling timely interventions.For instance, machine learning models trained on patient data can identify subtle physiological changes that may precede a critical event, offering nurses an invaluable "early warning system."Moreover, AI can also help create a better overview of the increasing amount of data clinicians need to deal with to optimize their workflow.It can be used to highlight personal rather than general trends and reduce preparation time, allowing more time to be spent on the patient 12 .In disease management and clinical training 13 , AI-powered tools can help support for nurses in creating individualized care plans.By analyzing a broad spectrum of data, including lifestyle factors, comorbidities, and treatment histories, AI can recommend interventions tailored to the unique needs of each patient or identify those at heightened risk.A notable example is in the management of patients HISTORICAL

Authors

Institutions

Publication Details

Journal
Texto & Contexto - Enfermagem
Published
2025-01-01
DOI
https://doi.org/10.1590/1980-265x-tce-2025-e001en
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ARTIFICIAL INTELLIGENCE IN NURSING: DRIVING A NEW STANDARD IN PATIENT CARE

Rogério Pessoto Hirata, Thomas Kronborg, Clara Bender, Simon Lebech Cichosz
1 citations
Texto & Contexto - Enfermagem
Artificial Intelligence in Healthcare and Education
0.65
article

ARTIFICIAL INTELLIGENCE IN NURSING: DRIVING A NEW STANDARD IN PATIENT CARE

Rogério Pessoto Hirata, Thomas Kronborg, Clara Bender, Simon Lebech Cichosz
article en
1 citations

Abstract

In the recent decade, artificial intelligence (AI) has emerged as a transformative force in healthcare, promising to enhance patient outcomes through predictive analytics, personalized care, and streamlined workflows 1,2 .For nursing professionals, integrating AI into clinical practice is not just a technological evolution -it represents an unrealized opportunity to reinforce the human-centric mission of care with powerful data-driven insights 3 .AI should not be viewed as a replacement but rather as a complement to nursing care 4 .Figure 1 illustrates an overview of areas where AI have potential to improve status quo and major challenges with the use and implementation of AI 5 .AI's ability to analyze large datasets and identify patterns has the potential to revolutionize decision-making in clinical care.Predictive analytics can help nurses anticipate complications 6 , such as sepsis 7 , foot ulcers development in diabetes 8 , in-hospital falls injuries 9 , or exacerbation in chronic obstructive pulmonary disease 10,11 , enabling timely interventions.For instance, machine learning models trained on patient data can identify subtle physiological changes that may precede a critical event, offering nurses an invaluable "early warning system."Moreover, AI can also help create a better overview of the increasing amount of data clinicians need to deal with to optimize their workflow.It can be used to highlight personal rather than general trends and reduce preparation time, allowing more time to be spent on the patient 12 .In disease management and clinical training 13 , AI-powered tools can help support for nurses in creating individualized care plans.By analyzing a broad spectrum of data, including lifestyle factors, comorbidities, and treatment histories, AI can recommend interventions tailored to the unique needs of each patient or identify those at heightened risk.A notable example is in the management of patients HISTORICAL

Texto & Contexto - EnfermagemVol. 34
Aalborg University (DK)
Openalex Percentile: Top 25%
Artificial Intelligence in Healthcare and Education
0.65
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.