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Timely prediction of lung cancer is essential to enable early intervention by healthcare professionals, enhancing patient outcomes and saving lives. This study introduces a comprehensive Machine Learning (ML) model designed to predict lung cancer at an early stage, utilizing a dataset sourced from Kaggle. Built on the Random Forest algorithm, the model assesses a diverse set of characteristics and variables, including gender, age, and exposure to various environments and lifestyles. It accurately identifies individuals at a higher risk of developing early-stage lung cancer, facilitating prompt intervention and personalized treatment strategies. Key evaluation metrics demonstrating the model's effectiveness include precision, F1 score, recall, and accuracy. The findings indicate a model accuracy of approximately 97.9%, underscoring its potential as a valuable tool for enhancing the early detection of lung cancer.<\/jats:p>","DOI":"10.1007\/s44163-024-00204-6","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T03:48:17Z","timestamp":1732679297000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["ML-based early detection of lung cancer: an integrated and in-depth analytical framework"],"prefix":"10.1007","volume":"4","author":[{"given":"Yusupha","family":"Sinjanka","sequence":"first","affiliation":[]},{"given":"Veerpal","family":"Kaur","sequence":"additional","affiliation":[]},{"given":"Usman Ibrahim","family":"Musa","sequence":"additional","affiliation":[]},{"given":"Karandeep","family":"Kaur","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,27]]},"reference":[{"key":"204_CR1","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.trsl.2017.02.004","volume":"184","author":"J Maddatu","year":"2017","unstructured":"Maddatu J, Anderson-Baucum E, Evans-Molina C. Smoking and the risk of type 2 diabetes. Transl Res. 2017;184:101\u20137. https:\/\/doi.org\/10.1016\/j.trsl.2017.02.004.","journal-title":"Transl Res"},{"key":"204_CR2","doi-asserted-by":"publisher","DOI":"10.53730\/ijhs.v6nS2.8306","author":"CS Anita","year":"2022","unstructured":"Anita CS, et al. Lung cancer prediction model using machine learning techniques. Int J Health Sci. 2022. https:\/\/doi.org\/10.53730\/ijhs.v6nS2.8306.","journal-title":"Int J Health Sci"},{"key":"204_CR3","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-6648-6_11","volume-title":"Prediction of lung cancer using machine learning classifier","author":"R Patra","year":"2020","unstructured":"Patra R. Prediction of lung cancer using machine learning classifier. Springer Singapore: Singapore; 2020."},{"issue":"1","key":"204_CR4","doi-asserted-by":"publisher","first-page":"45","DOI":"10.5114\/wo.2021.103829","volume":"25","author":"KC Thandra","year":"2021","unstructured":"Thandra KC, et al. 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