MEDICINE USAGE DATA ANALYSIS PYTHON

Predicting outcomes from static datasets is relatively less complex compared to handling dynamic datasets that arrive continuously, often referred to as data streams.Such streams play a vital role in applications like customer behavior prediction, product recommendation systems, and medical decision support.However, in the current environment, there is no system that processes real-world data on medicines sold across cities to analyze and predict drug usage patterns over time from different perspectives.To address this gap, we propose a machine learning-based system capable of processing large-scale medical datasets to identify consumption patterns, predict future demand, and support healthcare planning.The objective is to explore automated methods for data collection, extraction, analysis, and validation to strengthen public health surveillance and monitoring, including epidemiological and social studies