Are Machine Learning Methods the Future for Smoking Cessation Apps?

Smoking cessation apps provide efficient, low-cost and accessible support to smokers who are trying quit smoking. This article focuses on how up-to-date machine learning algorithms, combined with the improvement of mobile phone technology, can enhance our understanding smoking behaviour development advanced apps. In particular, we focus pros cons existing approaches that have been used in design date, highlighting need improve performance these by minimizing reliance self-reporting environmental conditions (e.g., location), craving status and/or events as a method data collection. Lastly, propose making use more methods while enabling processing information about user’s circumstances real time is likely result dramatic behaviour, also increasing effectiveness ease-of-use apps, provision timely, targeted personalised intervention.