id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-323074-u3bs5sj0	Garcia, L. P.	ESTIMATING UNDERDIAGNOSIS OF COVID-19 WITH NOWCASTING AND MACHINE LEARNING: EXPERIENCE FROM BRAZIL	2020-07-02		.txt	text/plain	3795	280	55	This study aimed to analyze the underdiagnosis of COVID-19, through nowcasting with machine learning, in a South of Brazil capital. To analyze the underdiagnosis, we compared the difference between the data without nowcasting and the median of the nowcasted projections for the entire period and for the six days from the date of onset of symptoms to diagnosis at the moment of data extraction. To help overcome this challenge, the present study aimed to analyze the underdiagnosis of COVID-19 cases, through nowcasting with machine learning, in a South of Brazil capital city. The following variables were extracted from anonymized database of suspected and confirmed cases: i) diagnostic (confirmed, discarded or missing), ii) sex, iii) age (in years), The number of infected people (with a positive diagnosis and less than 14 days of symptom onset) and the rate of infected people per 100,000 inhabitants were calculated for the health regions where each notified person resides.	./cache/cord-323074-u3bs5sj0.txt	./txt/cord-323074-u3bs5sj0.txt