The Application of AI in Clinical Nursing, Yields Several Advantageous Outcomes DOI
Habib Ahmed,

Naeema Akber,

Mohammad Saleem

и другие.

Indus journal of bioscience research., Год журнала: 2025, Номер 3(2), С. 591 - 599

Опубликована: Март 6, 2025

AI applications in nursing practice deliver transformative improvements for patient care while reducing workflow disruptions and serving healthcare workers better. This research explores how helps professionals through clinical decision systems as well observation workload optimization mental health resource delivery. Through their integration of support tools predictive analytics along with automation technologies experience better efficiency together lower administrative burdens improved safety. The use delivers individualized to nurses that enable them protect themselves from burnout stress. adoption technology faces crucial ethical obstacles include privacy risks related information systemic bias within algorithms social repercussions deployment. complete benefits depend on an equilibrium between technological progress patient-focused approaches. future success depends the education into curricula preparation AI-driven environments. demonstrates enables transformation but calls monitoring practices continuous assessment produce fair effective deployment outcomes.

Язык: Английский

Precision Management in Chronic Disease: An AI Empowered Perspective on Medicine-Engineering Crossover DOI Creative Commons
Chaoqun Dong, Yan Ji,

Zhongmin Fu

и другие.

iScience, Год журнала: 2025, Номер 28(3), С. 112044 - 112044

Опубликована: Фев. 17, 2025

Язык: Английский

Процитировано

1

The Role of Personality Traits in Nursing Students’ Attitudes Toward Artificial Intelligence DOI Open Access

Areti Tsiara,

Vissarion Bakalis, Aikaterini Toska

и другие.

Cureus, Год журнала: 2025, Номер unknown

Опубликована: Фев. 11, 2025

This study assesses nursing students' attitudes toward artificial intelligence (AI) and examines the role of personality traits in shaping these attitudes. Methods: A cross-sectional was conducted which 159 students from University Thessaly participated. Data were collected using General Attitudes Toward Artificial Intelligence Scale (GAAIS) to measure AI Ten Item Personality Inventory (TIPI) assess traits. Statistical analysis included descriptive inferential methods, such as correlation factor analysis. The significant level set p<0.05. Results: findings revealed moderately positive (mean attitude score: 3.22 out 5). Extraversion openness experience positively correlated with attitudes, while maternal education significantly associated lower negative Conclusion: Nursing demonstrate a cautious optimism AI, playing key their perceptions. Addressing concerns about through targeted educational programs could enhance confidence willingness adopt professional practice. These emphasize importance integrating into curricula bridge knowledge gaps promote effective use technologies healthcare.

Язык: Английский

Процитировано

0

The Application of AI in Clinical Nursing, Yields Several Advantageous Outcomes DOI
Habib Ahmed,

Naeema Akber,

Mohammad Saleem

и другие.

Indus journal of bioscience research., Год журнала: 2025, Номер 3(2), С. 591 - 599

Опубликована: Март 6, 2025

AI applications in nursing practice deliver transformative improvements for patient care while reducing workflow disruptions and serving healthcare workers better. This research explores how helps professionals through clinical decision systems as well observation workload optimization mental health resource delivery. Through their integration of support tools predictive analytics along with automation technologies experience better efficiency together lower administrative burdens improved safety. The use delivers individualized to nurses that enable them protect themselves from burnout stress. adoption technology faces crucial ethical obstacles include privacy risks related information systemic bias within algorithms social repercussions deployment. complete benefits depend on an equilibrium between technological progress patient-focused approaches. future success depends the education into curricula preparation AI-driven environments. demonstrates enables transformation but calls monitoring practices continuous assessment produce fair effective deployment outcomes.

Язык: Английский

Процитировано

0