Symptom-Based Medicine Recommendations Used in Natural Language Processing

Abstract

Since ancient times, viral illnesses have been at war with people. However, every living thing in the world—including tiny viruses—constantly strives for survival, according to the idea of evolution. Consequently, the burden of sickness and mortality caused by the transmission of infection by viruses to people is significant. Viruses are quickly developing on a daily basis. Although we have numerous cutting-edge methods for the detection, prevention, and treatment of infectious illnesses today, the introduction of new diseases continues to pose a severe threat to the health of the entire world's population. The new virus COVID-19 is a recent example. Because doctors were not aware of this illness at the time, many individuals perished. There are also many people who are financially strapped and unable to visit a doctor. We developed this system after studying these. Through this, we provide fundamental medical advice depending on the patient's numerous symptoms. In addition, we have developed a concept that can advance the pharmaceutical sector. We can use machine learning techniques to implement this strategy. yet, medical professionals are known for having sloppy cursive writing. About 7,000 fatalities per year in the United States are attributed to the inability to comprehend doctors' handwritten prescriptions. The issue ought to be worse because more doctors in Bangladesh and other least-developed countries write their prescriptions by hand. Because of this, both patients and pharmacists have trouble reading, and they frequently give the wrong drugs. In order to make it simpler to read prescriptions written by doctors, this study provides an offline handwritten prescription recognition system. For this study, samples of prescription' and medicine information were gathered from the Medex website and medical representatives in Noakhali city.