Medical Xpress July 21, 2025
Research in the International Journal of Data Mining and Bioinformatics discusses a new approach to demand forecasting for the pharmaceutical retail sector based on an artificial intelligence model. The findings hold promise for improving accuracy in one of the industry’s most persistent logistical challenges: managing sales that swing sharply during promotional periods. The new system works better than traditional models by distinguishing between routine demand and the short-term surges driven by marketing campaigns.
The team has built their forecasting system using a machine-learning framework known as the Temporal Fusion Transformer. This deep-learning model is designed specifically to analyze time-series data, such as daily sales figures or seasonal illness rates. Where conventional systems might smooth over the spikes and troughs in...
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