id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
futech-526	Wanigasingha, NH; Harshini, HGL; Ariyaratne, MKA; Fernando, TGI; Dikwatta, U. ; Samarasinghe, U.S. 	GI meets AI: Glycemic index in the age of AI, computational breakthroughs	2025	34	.pdf	application/pdf	32787	1785	42	By integrating XAI into GI prediction models, researchers can improve transparency and trust while uncovering the factors driving glycemic variability, such as food preparation methods, ripeness, and individual metabolic responses. • High GI foods (GI ≥ 70): These lead to rapid spikes in blood sugar (e.g., white bread, sugary drinks, and processed cereals).	cache/futech-526.pdf	txt/futech-526.txt