Role of big data in enhancing lung cancer prediction and treatment
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.4.11Keywords:
Lung Cancer, Big Data Analytics, Machine Learning, Early Detection, Predictive Modeling, Deep LearningDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Lung cancer functions as one of the world's primary diseases which causes death because patients receive their diagnoses too late and have limited choices regarding treatment. The research examines big data functionality for lung cancer prediction through extensive evaluation of patient healthcare records and image data along with hereditary information to establish predictive models. Evaluation of deep learning and ensemble techniques as well as additional machine learning algorithms takes place to measure their accuracy rates and operational efficiency.Abstract
How to Cite
Downloads
Similar Articles
- S. Vanaja, Hari Ganesh S, Application of data mining and machine learning approaches in the prediction of heart disease – A literature survey , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Temesgen A. Asfaw, Deep learning hyperparameter’s impact on potato disease detection , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- S ChandraPrabha, S. Kantha Lakshmi, P. Sivaraaj, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Adedotun Adedayo F, Odusanya Oluwaseun A, Adesina Olumide S, Adeyiga J. A, Okagbue, Hilary I, Oyewole O, Prediction of automobile insurance fraud claims using machine learning , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Lakshminarayani A, A Shaik Abdul Khadir, A blockchain-integrated smart healthcare framework utilizing dynamic hunting leadership algorithm with deep learning-based disease detection and classification model , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- J. Suvetha, Dr. S. Kumaravel, Development of an Ayurveda-Integrated Feature Engineering Framework for Disease Prediction , The Scientific Temper: Vol. 17 No. 03 (2026): The Scientific Temper
- S. Udhaya Priya, M. Parveen, ETPPDMRL: A novel approach for prescriptive analytics of customer reviews via enhanced text parsing and reinforcement learning , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- Deepa Ramachandran VR VR, Kamalraj N, Hybrid deep segmentation architecture using dual attention U-Net and Mask-RCNN for accurate detection of pests, diseases, and weeds in crops , The Scientific Temper: Vol. 16 No. 07 (2025): The Scientific Temper
- S. C. Prabha, P. Sivaraaj, S. Kantha Lakshmi, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Hardik Talsania, Kirit Modi, Attention-Enhanced Multi-Modal Machine Learning for Cardiovascular Disease Diagnosis , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.

