Artificial intelligence in nursing: an integrative review of clinical and operational impacts by Salwa Hassanein, Salwa Hassanein, Rabie Adel El Arab, Rabie Adel El Arab, Amany Abdrbo, Mohammad S. Abu-Mahfouz, Mastoura Khames Farag Gaballah, Mohamed Mahmoud Seweid, Mohamed Mahmoud Seweid, Mohammed Almari, Husam Alzghoul

“…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”
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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…Virtual hospitals that are powered by AI have shown remarkable enhancements in the accessibility of healthcare services. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…Eur Eat Disord Rev 2023) and ECHO-based (Philipp J, Truttmann S, Zeiler M, Franta C, Wittek T, Schöfbeck G, et al. Reduction of high expressed emotion and treatment outcomes in anorexia nervosa – caregivers’ and adolescents’ perspective. …”
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Enactivism, Health, AI, and Non-Neurotypical Individuals: Toward Contextualized, Personalized, and Ethically Grounded Interventions by Jordi Vallverdú

“…The enactive approach offers a powerful theoretical lens for designing artificial intelligence (AI) systems intended to support the health and well-being of non-neurotypical individuals, including those on the autism spectrum and those with with ADHD, dyslexia, or other forms of neurodivergence. …”
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A Survey on UAV Control with Multi-Agent Reinforcement Learning by Chijioke C. Ekechi, Tarek Elfouly, Ali Alouani, Tamer Khattab

“…Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in both governmental and civilian applications, offering significant reductions in operational costs by minimizing human involvement. …”
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EXPLORING AUTOMATED SUMMARIZATION: FROM EXTRACTION TO ABSTRACTION by Svetlana G. Sorokina

“…This paper provides a review of AI-powered automated summarization models, with a focus on two principal approaches: extractive and abstractive. …”
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Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning by Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang

“…While deep learning-based computer vision techniques have emerged as powerful tools for crop disease recognition, these methods are heavily reliant on large datasets, which are often difficult to obtain in practical agricultural settings. …”
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Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions by Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Mette Sagbakken, Ahmed Ghannam, Fuad H. Abuadas, Joel Somerville, Joel Somerville, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair

“…These efficiencies allowed nursing teams to devote more time to direct patient care and were associated with reductions in burnout and improved workplace morale.Nursing perceptionsAcross practice settings, nursing students and practicing nurses broadly welcomed AI’s ability to streamline workflows and support decision-making, recognizing its potential to elevate patient care and professional practice.Ethical implicationsSimultaneously, nurses voiced significant ethical concerns—chiefly around safeguarding patient data privacy, mitigating algorithmic bias, and preserving the compassionate, human-centered essence of nursing in an increasingly automated environment.Framework and recommendationsThe Nursing AI Integration Roadmap (NAIIR) was developed, emphasizing transformational education, advanced clinical integration, ethical governance, robust organizational infrastructure, participatory design, and rigorous economic evaluation. …”
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