Introducing Text Analysis Algorithms in Decision Support Systems for Automated Evaluation of the Doctor Prescriptions

Artificial Intelligence (AI) and Natural Language Processing (NLP) emerged as the powerful tools in the healthcare sector offering potential to revolutionize patient care through efficient and accurate analysis of the unstructured text data, particularly the electronic health records (EHRs). Recognizing the critical role of adherence to the established standards in healthcare, the article introduces the Doctor Prescription Evaluation System. This software design aims to assess compliance of the doctors prescriptions with these standards, ultimately enhancing the patient care. The proposed model employs CountVectorizer and supervised machine learning algorithms to map the input text in the output labels. By providing a comprehensive overview of the software algorithm, the article meticulously analyzes each step and unravels the fundamental mechanisms driving its functionality. The findings of this study expose the system's ability to accurately evaluate and analyze doctor prescriptions, enabling efficient decision-making and ensuring high-quality patient care.