Clinical assistant on the front line of decision-making: How does artificial intelligence help improve the quality of services to the treatment team?
Code: G-1719
Authors: Vida Shafipour * ℗, Leila Shafipour
Schedule: Not Scheduled!
Tag: Clinical Decision Support System
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Abstract:
Abstract
Background and aims: Providing healthcare services on the front lines of encountering patients inside or outside the hospital is a vital priority. Given the existing infrastructure in Iran's healthcare sector, it is very important to answer the question of how artificial intelligence can be used to make important treatment decisions in the golden times of care and treatment? Method: First, to collect information on the use of artificial intelligence in providing services, reliable and accessible databases such as CINAHL, Scopus, Web of Science, PubMed, Medline, Irandoc, Magiran, and SID were used. The search was conducted with the keywords artificial intelligence, providing services, hospital, emergency, patients, staff, nurses, and doctors between 2020 and 2025. Of the 16 relevant articles, 7 were used that were appropriate for the purpose of the study. Results: The results of the studies showed that artificial intelligence can help the treatment team make appropriate and timely decisions by analyzing patient data and identifying disease patterns. It can also be very useful by designing automated triage systems by predicting the number of patients and allocating facilities correctly to prioritize services. It can also be helpful in accessing essential medical information; training and simulation to strengthen skills in triage and crisis management for treatment staff; and by embedding decision support systems. Conclusion: Therefore, given the valuable role of using artificial intelligence technology in the context of care and treatment, it is necessary to employ experts in this treatment context and benefit from interdisciplinary cooperation with the treatment team in order to provide acceptable and effective quality services to the community.
Keywords
Clinical Assistant, Artificial Intelligence, Clinical Decision
