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Journal of Medical Surgical & Forensic Nursing

Volume 1, Issue 1, 2025
Mcmed International
Journal of Medical Surgical & Forensic Nursing
Issn
3117-4280 (Print), 3117-4299 (Online)
Frequency
bi-annual
Email
editorJMSFN@mcmed.us
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Abstract
Title
INTEGRATING ARTIFICIAL INTELLIGENCE IN SURGICAL NURSING: ENHANCING CLINICAL DECISION-MAKING AND PATIENT OUTCOMES
Author
Amit Kumar Meena
Email
keyword
Artificial Intelligence, Surgical Nursing, Clinical Decision-Making, Patient Outcomes, Predictive Analytics, Perioperative Care, Intraoperative Monitoring, Postoperative Recovery, Robotic Surgery, Nursing Informatics, Healthcare Ethics, Data Privacy, Di
Abstract
Artificial Intelligence (AI) has become a defining innovation in healthcare, driving a paradigm shift in how clinical decisions are made, how surgical teams operate, and how patient care is delivered. Within the highly complex and sensitive domain of surgical nursing, AI provides a powerful set of tools that help nurses to predict complications, monitor patients in real time, and personalize treatment strategies. Unlike traditional methods where nurses rely solely on clinical experience and manual observation, AI integrates vast datasets—including patient histories, lab reports, imaging scans, and intraoperative signals—to generate predictive insights that improve safety and efficiency. This paper explores how AI can be systematically integrated into surgical nursing, focusing on three critical domains: perioperative care planning, intraoperative monitoring, and postoperative recovery management. Through case studies, data analysis, and questionnaires, the study demonstrates how AI enhances nursing competence, reduces human error, and improves patient outcomes. The research also emphasizes the importance of balancing technological innovation with ethical safeguards, data privacy protocols, and continuous training for surgical nurses. Ultimately, AI is not a replacement but asupportive ally that complements the judgment, empathy, and expertise of surgical nurses
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