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Sumit Padihar

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Open access Aug 2026

ARTIFICIAL INTELLIGENCE IN NURSING PRACTICE: TRANSFORMING PATIENT CARE, CLINICAL DECISION MAKING, AND NURSING EDUCATION

Artificial Intelligence (AI) is rapidly transforming healthcare by supporting clinical decision-making, improving patient safety, streamlining documentation, and strengthening nursing education. Nursing professionals are increasingly using AI-enabled technologies such as clinical decision-support systems, predictive analytics, virtual assistants, remote patient monitoring, natural language processing, robotics, and intelligent electronic health records. These technologies can assist nurses in identifying patient deterioration, prioritizing care, reducing medication errors, managing large volumes of clinical information, and developing individualized care plans. In nursing education, AI provides opportunities for adaptive learning, virtual simulation, automated assessment, personalized feedback, and development of clinical reasoning skills. However, successful implementation requires attention to ethical issues, data privacy, algorithmic bias, cybersecurity, professional accountability, technological literacy, and the preservation of human-centered care. Nurses must therefore develop appropriate AI literacy while maintaining critical thinking and clinical judgment. This article discusses the role of AI in nursing practice, its impact on patient care and clinical decision-making, applications in nursing education, advantages, challenges, ethical considerations, and future implications for the nursing profession.

Sumit Padihar, Sunita Joshi, Ratna Parmar et al. · 0 citations
Review Open access Aug 2026

Artificial Intelligence In Mental Health Nursing: Applications, Opportunities, Ethical Challenges, And Future Directions

AI should be regarded as a supportive technology rather than a replacement for professional nursing judgment or human therapeutic relationships, particularly regarding privacy, confidentiality, informed consent, algorithmic bias, transparency, accountability, patient safety, therapeutic relationships, and the risk of over-reliance on automated systems.

Payal Sharma, Milan Agravat, Pranali Mackwan et al. · 0 citations

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