Due to advancements in computer vision techniques, medical healthcare data
is available to users in a very large amount. With the use of this data, an intelligent
medicine recommendation system can be prepared. Authors in this chapter utilized
Term Frequency-Inverse Document Frequency (TF-IDF) and Machine Learning (ML)
for the development of an intelligent medicine recommendation system. The
recommendation system recommends proper medicines by exploring the symptoms of
patients and their medical history. The TF-IDF technique retrieves suitable features
from the dataset and then applies machine learning for the classification of diseases and
the recommendation of medicine to patients. The proposed recommendation system
provides valuable and accurate suggestions to users, adding flexibility to the healthcare
system.
Keywords: Medicine recommendation, Disease symptoms, Term FrequencyInverse Document Frequency (TF-IDF), Machine Learning (ML).
