Applications of Artificial Intelligence in Nursing Diagnosis and Nursing Care

Artificial intelligence (AI) is increasingly being integrated into healthcare and nursing practice. This article reviews the application of AI across the nursing process, with particular emphasis on assessment, nursing diagnosis, care planning, clinical decision support, patient monitoring, documentation, and evaluation of outcomes. Recent evidence indicates that machine learning, natural language processing, predictive analytics, and generative AI can analyze large volumes of structured and unstructured clinical data, identify patterns associated with nursing problems, support risk prediction, and generate preliminary care-plan content. AI-supported systems may improve decision-making, workflow efficiency, documentation quality, and early detection of patient deterioration. Nevertheless, current evidence remains limited by heterogeneous methods, relatively few real-world implementation studies, algorithmic bias, limited interpretability, privacy concerns, alert fatigue, and the risk of automation bias. AI should therefore be implemented as a decision-support technology rather than a substitute for professional nursing judgment. Nurse participation in system design, rigorous clinical validation, transparent governance, data protection, interoperability, and AI literacy are essential for safe implementation. The future of AI in nursing is best understood as a human–AI partnership in which computational capabilities augment, rather than replace, clinical reasoning and compassionate patient-centered care.

کلیدواژه ها:

Artificial intelligence ، Nursing diagnosis ، Nursing care ، Nursing process ، Machine learning ، Clinical decision support ، Natural language processing ، Nursing informatics ، Generative AI ، Patient safety