Title: Analyzing the Relationship between Smoking and Drinking Patterns Using Neural Networks: A Comprehensive Feature-Based Approach
Authors: Ahmed Samir Abu Al-Hussein
Mona Ayman Abu Aisha
Iman Nahed Saeed Ahleel
Samy S. Abu-Naser
Volume: 7
Issue: 9
Pages: 18-25
Publication Date: 2023/09/28
Abstract:
This study employs a neural network to analyze the connection between smoking, drinking, and various health-related factors using a dataset of 5148 samples. Achieving an impressive 99.94% accuracy and an average training error of 0.0016, the model identifies influential factors such as serum aminotransferases, serum creatinine, sex, weight, and triglyceride levels. These findings enhance our understanding of lifestyle choices and their impact on health. This research underscores the potential of machine learning in studying complex health phenomena.