id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
futech-646	Zhou, Nan; Ng, Teck Han; Foo, Chai Nien; Ling, Lloyd; Lim, Yang Mooi	Machine learning model for predicting symptom improvement rates in hospitalized deep vein thrombosis patients	2025	9	.pdf	application/pdf	5970	298	39	The 30% threshold follows established guidelines for clinical prediction models. 561-569, 2016. doi:10.2147/ppa.s104446 [26] A. Abdel-Hafez et al., Predicting therapeutic response to unfractionated heparin therapy: machine learning approach, Interactive Journal of Medical Research, vol. 11, no. 2, p. e34533, 2022. doi:10.2196/34533 [27] A. Shaikh et al., Six-month outcomes of mechanical thrombectomy for treating deep vein thrombosis: analysis from the 500-patient CLOUT registry, Cardiovascular and interventional radiology, vol. 46, no. 11, pp.	cache/futech-646.pdf	txt/futech-646.txt