Enhancing patient outcomes through machine learning: A study of lung cancer prediction

Abstract

This study intends to investigate how machine learning methods may be used to predict lung cancer. Early detection can considerably improve patient outcomes because lung cancer is the leading cause of cancer-related deaths worldwide. The study focuses on the investigation of several risk variables and biomarkers, including smoking history, age, and family history, that can affect the development of lung cancer. The research analyses the performance of the most recent machine learning algorithms for lung cancer prediction using a considerable. dataset of patient records. The findings show that machine learning algorithms can accurately and precisely forecast the likelihood of developing lung cancer. The study sheds light on the potential of machine learning in enhancing lung cancer screening and preventive methods and offers information on the creation of patient-specific tailored treatment plans.