Medical Prescription Generator using Natural Language Processing

With the increasing population in India and the limited availability of medical professionals, time efficiency in diagnosis and prescription generation has become crucial. This paper proposes an automated system leveraging Natural Language Processing (NLP) and Natural Language Generation (NLG) to assist doctors in generating patient history and prescription suggestions. The system utilizes previously typed words to predict the next word, drawing on a medical notes dataset tailored to the doctor’s specialization. By giving keywords or short descriptions about a patient’s condition, the system processes the input using NLP for contextual under-standing and employs NLG to generate detailed histories and prescriptions in a standardized format. This dual approach ensures that the output aligns with medical conventions while maintaining accuracy and efficiency. The system is trained on extensive medical datasets, optimizing its predictions over time through machine learning techniques. Our solution not only enhances accuracy but also reduces the time doctors spend on manual documentation, improving overall efficiency and patient care.