Machine Learning (ML) has been a disruptive factor in many industries in recent years. This blog article explores two areas where machine learning (ML) is making great progress: Internet of Drones (IoD) and tobacco research. Despite their apparent differences, these domains are united by the advancement and creativity brought about by cutting-edge data analysis methods.
Machine Learning for Research on Tobacco:
A scoping assessment was carried out by Rui Fu and associates to assess the influence of machine learning on tobacco research. Their thorough analysis, which was published in the journal Tobacco Control, found 74 studies that used machine learning techniques. Four unique domains were identified from these studies:
1. ML-powered smoking cessation technology (n = 22)
2. Content analysis (n=32) of data on tobacco use on social media platforms
3. Classifying smokers using narrative clinical materials
4. Prediction of outcomes related to tobacco use based on administrative, survey, or clinical trial data (n=14)
This review demonstrates the enormous potential of machine learning to advance tobacco control initiatives and influence policy choices.
ML in Quitting Smoking:
Machine learning applications have demonstrated potential in offering tailored interventions in the field of smoking cessation. ML algorithms have the capability to customize tactics to enhance the probability of stopping by examining individual smoking behaviors and aspects that contribute to the success of cessation. These technological advancements not only empower individuals but also improve the overall effectiveness of smoking cessation programs.
