id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-4811	D. Kumaresan, B. Santhosh Kumar	A Comparative Study on Prediction Efficiency in Lung Cancer Detection Using Machine Learning Models	2025	11	.pdf	application/pdf	3465	206	44	Examined the use of radiomic features in lung cancer prediction and the importance of selecting the most relevant variables. This analysis highlights that J48 and Random Forest are the most efficient models for lung cancer prediction, delivering the highest accuracy and lowest error metrics with minimal training time.	cache/cana-4811.pdf	txt/cana-4811.txt