id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-5666	URAL, Ali Berkan ; KOÇ, Evren 	Analysis of obesity statuses on rats using blood test parameters: A feasibility study	2025	10	.pdf	application/pdf	5182	264	43	The proposed methodology involves collecting blood samples from obese and normal (control group) rats, extracting key metabolic parameters, and utilizing machine learning models to classify https://orcid.org/0000-0001-5176-9280 https://orcid.org/0000-0002-0022-9433 1666 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 3: 1665-1674, 2025 DOI: 10.55214/25768484.v9i3.5666 © 2025 by the authors; licensee Learning Gate obesity status. [14] V. Osadchiy et al., Machine learning model to predict obesity using gut metabolite and brain microstructure data, Scientific Reports, vol. 13, no. 1, p. 5488, 2023. https://doi.org/10.1038/s41598-023-32313-4	cache/easat-5666.pdf	txt/easat-5666.txt