Background: Telemedicine has emerged as an essential instrument in healthcare, particularly during situations necessitating swift surgical operations. Telemedicine in emergency surgeries encounters obstacles, including as delays in decision-making, inefficiencies in data administration, and communication hurdles. Artificial intelligence (AI) addresses these challenges by streamlining procedures, augmenting diagnostic precision, and refining
decision support systems. This systematic review seeks to assess the utilization of
artificial intelligence in enhancing
telemedicine procedures for emergency surgeries. Materials and Methods: A comprehensive search was performed in the PubMed, Scopus, Web of Science, and IEEE Xplore databases for studies published from January ۲۰۱۰ to October ۲۰۲۳. Keywords encompassed "artificial intelligence," "telemedicine," "emergency surgery," "optimization," and "decision support." The inclusion criteria comprised peer-reviewed research addressing AI applications in
telemedicine for emergency operations, whereas the exclusion criteria encompassed non-English articles, conference abstracts, and studies without a clear emphasis on emergency surgeries. The Cochrane Risk of Bias tool was employed to evaluate randomized trials, while ROBINS-I was utilized for observational studies. Results were integrated utilizing narrative and meta-analytical methodologies where relevant. Results: ۴۲ studies encompassing ۳,۶۱۵ people were included. The majority of research deployed machine learning models (n=۲۸) for triage and diagnostic assistance, while some employed natural language processing (n=۹) for real-time communication and deep learning (n=۵) for image analysis. AI-enhanced solutions decreased decision-making durations by an average of ۳۷% (۹۵% CI: ۳۰%-۴۴%) and augmented diagnostic precision by ۲۱% (۹۵% CI: ۱۵%-۲۷%) relative to conventional
telemedicine procedures. Nonetheless, issues including bias in AI models and insufficient data standards were observed. Conclusion: Artificial intelligence markedly enhances
telemedicine procedures for emergency surgeries by augmenting efficiency, precision, and decision-making support. Notwithstanding its advantages, issues such as model bias and interoperability concerns require resolution. Subsequent study ought to concentrate on formulating standardized AI techniques and assessing long-term outcomes. This review highlights AI's capacity to revolutionize emergency surgical care via telemedicine.
