Aug 2026· Hu li za zhi The journal of nursing· Vol 73 4· 0 citations
Medicine
TL;DR
Evidence indicates that clinical decision support systems can enhance consistency in care processes, improve nurse recognition of patient deterioration, and support prioritization and interprofessional communication, and AI-driven early warning analytics can leverage high-dimensional clinical data to detect patient deterioration earlier, thereby improving patient safety and quality of care.
AI-CDSS should be regarded as tools that support, rather than replace, nursing clinical judgment, and safe and equitable implementation requires robust digital infrastructure, nurse education, local evaluation of system performance, multidisciplinary governance, and clear safeguards for privacy, transparency, accountab...
I. M, Bamigboye T. O., Oniyide A. A.· International journal of re...· 0 citations
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 are discussed.
Sumit Padihar, Sunita Joshi, Ratna Parmar et al.· Genetics and Molecular Resea...· 0 citations
Artificial intelligence (AI)-based clinical decision support systems (CDSS) are increasingly embedded in nursing workflows, promising earlier detection of patient deterioration, more efficient documentation, and more consistent risk stratification, yet the evidence base is fragmented across clinical domains and ethical...
I. M, Bamigboye T. O., Oniyide A. A.· International journal of re...· 0 citations
Clinical practice has transformed due to a surge in the development of artificial intelligence tools to support decision-making. AI-Assisted Clinical Decision Support (AI-CDS) is one of the most promising technological tools in improving care outcomes. AI-CDS tools are digital systems relying on artificial intelligence...
Dinah Limiri· Premier Journal of Science· 0 citations
The evidence indicates that AI can improve risk stratification, early recognition of clinical deterioration, medication-safety processes, documentation quality, and access to simulation-based education, and support a human-in-the-loop model in which AI augments rather than replaces nursing judgment.
Heloísa de Oliveira Nascimento· Nexus Science Review· 0 citations
AI-enabled clinical decision support systems (CDSS) have the potential to support the detection of patient deterioration, but their value depends on outputs that fit clinical workflows, support reasoning, and minimise alert fatigue. Little is known about clinician perspectives on Multi-Output Early Warning Systems (M...
Monica Noselli, A. H. van der Vegt, Maxime Cordeil et al.· Journal of Technology in Beh...· 0 citations
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