A Predictive Study on Aeroallergen Patterns in Durg-Bhilai, Optimising Allergy Management through Sequence Data Mining and Machine Learning

Abstract

This study explores the application of sequence data mining techniques and machine learning methodologies to analyze historical aeroallergen concentrations in the Durg-Bhilai region. By identifying distinct patterns in aeroallergen levels and employing machine learning models to forecast future trends, the research aims to optimize allergy management strategies. The integration of time-series data with advanced algorithms ensures accurate predictions, providing valuable insights for healthcare professionals and policymakers to mitigate allergy risks.This study explores the application of sequence data mining techniques and machine learning methodologies to analyze historical aeroallergen concentrations in the Durg-Bhilai region. By identifying distinct patterns in aeroallergen levels and employing machine learning models to forecast future trends, the research aims to optimize allergy management strategies. The integration of time-series data with advanced algorithms ensures accurate predictions, providing valuable insights for healthcare professionals and policymakers to mitigate allergy risks.