Journal of Angiotherapy
Integrative Biomedical Research | Online ISSN  2207-872X
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Contents Vol 8 (9)

Revolutionizing Emergency Medicine: The Integration of Artificial Intelligence and Predictive Analytics in Clinical Decision-Making and Training - A Comprehensive Review

Saud Tawfiq Al Shammari 1, Saad Mosluh Mohammed Alqahtani 1, Awwadh Saad Rashed Alshalawi 1, ‏Khalid Shaman M Almutairi 1, ‏Abdullah Thwab M Alotaibi 1, Majed Abdulrahman Bin Owaydhah Alsulami 1, Mohammed Rashed Mohammed Aldossari 1, ‏Khalid Hussain Saeed Alahmari 1, Khalid Abdulmohsen Saad Alanazi 1, Abdulrahman Bader O Alsulami 1*

+ Author Affiliations

Journal of Angiotherapy 8 (9) 1-8 https://doi.org/10.25163/angiotherapy.8910249

Submitted: 24 July 2024 Revised: 13 September 2024  Published: 15 September 2024 

Abstract

Emergency medicine is undergoing a transformative shift with the integration of Artificial Intelligence (AI) and predictive analytics into clinical practice. This review explores the applications, benefits, and challenges of AI in emergency care settings. AI technologies, including machine learning and natural language processing, are increasingly utilized to enhance triage systems, anticipate patient deterioration, and support clinical decision-making. Predictive models facilitate early detection and intervention for critical conditions such as sepsis and cardiac arrest, leading to improved outcomes and resource optimization. Additionally, AI-powered simulations and virtual reality platforms are advancing the training and preparedness of emergency care professionals. Despite these advancements, the implementation of AI is impeded by ethical concerns, trust and transparency issues, data privacy challenges, and disparities in technological accessibility. Furthermore, the lack of interpretability in AI-generated recommendations poses risks to clinical credibility and patient safety. Successful integration of AI into emergency medicine demands coordinated efforts among developers, healthcare providers, and policymakers. When thoughtfully applied, AI and predictive analytics hold the potential to significantly enhance the quality, efficiency, and effectiveness of emergency care. However, achieving widespread adoption requires overcoming technical, ethical, and educational barriers to foster trust and usability within the medical community.

Keywords: Artificial Intelligence, Predictive Analytics, Emergency Medicine, Clinical Decision Support, Healthcare Technology.

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