Medical Prescription using NLP Approaches: A Literature Review

Natural Language Processing (NLP) is revolutionizing medical prescription technology within the healthcare industry. This research endeavors to underscore the pivotal role of NLP, elucidating the methodologies employed to convert unstructured textual medical prescription data into structured information. This transformation facilitates personalized medication recommendations and enhances patient outcomes. The study delves into the challenges inherent in medical prescription contexts, examining existing literature and NLP applications aimed at mitigating these challenges. Additionally, it evaluates current systems for medical prescription to identify areas for improvement in healthcare operations. Highlighted in this paper are potential issues such as prescription errors and misuse, alongside the discussion of NLP's significance and its primary techniques in medical contexts. While NLP solutions have addressed some prescription challenges, further enhancements are warranted, as suggested by scholars advocating for advanced NLP techniques. In conclusion, this study emphasizes the techniques and applications of NLP in medical prescriptions, underscoring the need for continued research to refine NLP methodologies and optimize healthcare practices.