Artificial Intelligence In Emergency Medicine And It Impact On Patient Related Factors

Artificial Intelligence (AI) has transformed medicine by leveraging machine learning to analyze medical data, enhancing healthcare outcomes. From its roots in the ۱۹۵۰s to recent advancements in deep learning, AI's evolution has accelerated, particularly in emergency medicine. This review explores how AI influences patient-related factors in the emergency department, improving decision-making, disease diagnosis, and overall care quality. AI transforms emergency care by swiftly diagnosing and optimizing resource allocation. In prehospital settings, AI aids patient evaluation, ensuring timely treatment. Ethical considerations, like transparency and privacy, are pivotal in responsible AI integration, ultimately enhancing diagnostic capabilities and improving patient care in emergency rooms. Predictive analytics enhances patient care by forecasting outcomes and streamlining operations. AI image recognition improves diagnostic capabilities, while AI-powered chatbots offer real-time guidance in emergencies.. AI is reshaping patient care in Emergency Departments across key aspects: patient stratification, mortality analysis, and cost reduction. AI tools, employing sophisticated algorithms, enhance risk identification and resource allocation in patient stratification. In mortality analysis, AI applications show promise in hastening treatment, but ethical considerations remain paramount. Cost reduction is addressed through AI's efficiency improvements, decreased wait times, and optimal resource allocation, positively impacting patients' financial burdens.

کلیدواژه ها:

Artificial Intelligence ، Emergency medicine ، Patient related.