Open Access
Research Article
Enhancing patient outcomes through machine learning: A study of lung cancer prediction
Madhvan Bajajmadhvanbajaj.cst.ml.ai.20011249@gehu.ac.inDepartment of Computer Science and Engineering Graphic Era Hill UniversityDepartment of Computer Science and Engineering Graphic Era Hill UniversityDehradun, Uttarakhand, IndiaView full profile → , Priyanshu Rawatpriyanshurawat.cse.20011683@gehu.ac.inDepartment of Computer Science and Engineering Graphic Era Hill UniversityDepartment of Computer Science and Engineering Graphic Era Hill UniversityDehradun, Uttarakhand, IndiaView full profile → , *Satvik VatsCorresponding authorsvcse@mmmut.ac.inDepartment of Computer Science and Engineering Graphic Era Hill UniversityDepartment of Computer Science & Engineering Madan Mohan Malaviya University of TechnologyGorakhpur, Uttar Pradesh, 273010, India0000-0002-9422-4915View full profile → , Vikrant Sharmavsharma@gehu.ac.inDepartment of Computer Science and Engineering Graphic Era Hill UniversityDepartment of Computer Science and Engineering Graphic Era Hill UniversityDehradun, Uttarakhand, IndiaView full profile → , Shreshtha MehtaShreshtha.mehta12@gmail.comDepartment of Biotech Engineering Graphic Era (Deemed to be University) Dehradun, Uttarakhand, IndiaView full profile → , B. B. Sagarbbsagar@bitmesra.ac.inDepartment of Computer Science and Engineering Birla Institute of Technology, MesraRanchi, Jharkhand, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Published Online:
- 04 Sep 2023
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1438
- Pages:
- 1075–1086
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.
Keywords
Subject Classifications
68T07
References
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