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
- C. Agilan, Lakshna Arun, Optimization-based clustering feature extraction approach for human emotion recognition , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Ayesha Shakith, L. Arockiam, Enhancing classification accuracy on code-mixed and imbalanced data using an adaptive deep autoencoder and XGBoost , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Arvind K Shukla, Balaji V, Dharani R, M Ananthi, R Padmavathy, Romala V. Srinivas, Precision agriculture predictive modeling and sensor analysis for enhanced crop monitoring , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- L. Amudavalli, K. Muthuramalingam, Energy-efficient location-based routing protocol for wireless sensor networks using teaching-learning soccer league optimization (TLSLO) , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- K. Sreenivasulu, Sampath S, Arepalli Gopi, Deepak Kartikey, S. Bharathidasan, Neelam Labhade Kumar, Advancing device and network security for enhanced privacy , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Sachin V. Chaudhari, Jayamangala Sristi, R. Gopal, M. Amutha, V. Akshaya, Vijayalakshmi P, Optimizing biocompatible materials for personalized medical implants using reinforcement learning and Bayesian strategies , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- G. Chitra, Hari Ganesh S., Cultural algorithm based principal component analysis (CA-PCA) approach for handling high dimensional data , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- A. Sathya, M. S. Mythili, MOHCOA: Multi-objective hermit crab optimization algorithm for feature selection in sentiment analysis of Covid-19 Twitter datasets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- B. S. E. Zoraida, J. Jasmine Christina Magdalene, Smart grid precision: Evaluating machine learning models for forecasting of energy consumption from a smart grid , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- C. Muruganandam, V. Maniraj, A Self-driven dual reinforcement model with meta heuristic framework to conquer the iot based clustering to enhance agriculture production , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
<< < 10 11 12 13 14 15 16 17 18 19 > >>
You may also start an advanced similarity search for this article.

