id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-4845	Sanchita Pange, Vijaya Pawar	Depression Analysis and Diagnosis using Machine Learning	2025	15	.pdf	application/pdf	5687	324	51	[12] Support Vector Machine (SVM) (EEG Signals) - - 83.07 On a national and worldwide scale, research indicates that ECG signals have an accuracy of 93.96% and EEG signals have an accuracy of 95.3%. For EEG signals, the most important characteristics are Hjorth activity (HA), standard deviation, entropy, and band power alpha; for ECG signals, the arithmetic mean is important.	cache/cana-4845.pdf	txt/cana-4845.txt