The Advantage of Artificial Intelligence in Personalizing Empirical Treatments

Background and Aims: Recent progressions in artificial intelligence (AI) have transformed different aspects of medicine. One of its eminent applications is the personalization of empirical treatments for patients, which improves treatment precision and decreases adverses. This study aims to explore the benefits and impacts of using AI in personalizing empirical treatments. Methods: This research utilized a systematic review of proper studies on the use of AI in empirical treatments. Scientific resources were retrieved from databases including PubMed and Google Scholar. Inclusion criteria focused on studies that emphasized the personalization of medical treatments based on clinical data. Data were gathered from studies conducted over the past years and analyzed precisely. Results: The findings showed that AI models, using patients' clinical data, have increased the precision of selecting appropriate treatments for many diseases by up to ۳۰%. Additionally, decision-making time in clinical settings was significantly decreased, and patient safety was improved. These tools were particularly useful in complex cases where opposite clinical data existed. besides, AI showed its ability to adapt to dynamic clinical environments, further enhancing its utility in medical decision-making. Conclusion: AI has shown excellent potential in increasing the accuracy and efficiency of empirical treatments and can serve as an effective tool in clinical decision-making activities. Future researches are recommended to focus on better integration of this technology with available healthcare systems and address the ethical and legal challenges related with its implementation.

کلیدواژه ها:

Artificial Intelligence ، Empirical Treatment ، Personalization