A Comparative Study on Natural Language Processing Approaches for Medical Prescription Classification Using Deep Learning Techniques

In the medical field, knowing prescription drugs is essential to correctly diagnosing illnesses. Examining medical prescriptions has gained significance due to the rise in new diseases and prevalent health issues. This article investigates the application of natural language processing (NLP) and deep learning models in interpreting medical prescriptions, shedding light on the diverse methods and strategies involved. Researchers can effectively extract valuable information from prescription texts by employing deep learning algorithms and NLP techniques, leading to enhanced medication comprehension and categorization. The study emphasizes the essential roles of deep learning and NLP in analyzing prescription medications, assessing the effectiveness of these methods through various datasets and technological approaches. The review emphasizes how important they are to raising diagnostic and therapeutic efficacy. Using deep learning and text categorization techniques in prescription analysis improves patient outcomes and medical care, enhancing healthcare delivery and overall well-being.