Sayyaf Mohammed Alhazmi
General practitioner, Saudi Arabia
Publications
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Research Article
Assess Artificial Intelligence in Emergency Medicine for Better Patient Care: A Systematic Review
Author(s): Atef Eid Madkour Elsayeda*, Mohsin Shahabuddin, Abdulrahman Emad Shafie, Fadi Elshafi Babikir Mohammed*, Abid Waseem, Muneer Ahmed Mohammed Bakr, Waheed Ibrahim Mohamed Alasiri, Ghaliah Waleed Hamid Othman, Sayyaf Mohammed Alhazmi and Imtiaz Ahmed S/0 Muhammad Soomar Soomro
Background: Artificial intelligence (AI) has emerged as a transformative tool in emergency medicine, where timely and accurate decision-making is vital. Machine learning (ML), deep learning (DL), and natural language processing (NLP) approaches are increasingly applied to enhance triage, risk stratification, and prediction of adverse outcomes. Despite these advances, variability in methodologies and reported outcomes underscores the need for a systematic synthesis of the evidence. Objective: This systematic review evaluates the impact of AI in emergency medicine, focusing on its influence on triage accuracy, clinical outcomes, workflow efficiency, and overall patient care. Methods: The review was conducted in line with PRISMA 2020 guidelines. Eligible studies included randomized controlled trials, retrospective and.. Read More»