id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-260697-oepk0b1d	Huang, J.	COVID-19 Recurrent Varies with Different Combinatorial Medical Treatments Determined by Machine Learning Approaches	2020-08-01		.txt	text/plain	5734	353	50	We applied the Synthetic Minority Oversampling Technique (SMOTE) to overcome the rare recurring events in certain age groups and performed Virtual Twins (VT) analysis facilitated by random forest regression for medical treatment-recurrence classification. Here, we report the clinical, radiological, laboratory, and drug treatment findings of 93 recurring patients from 414 patients in Shenzhen, along with our machine learning approaches for identifying the best drug combinations that reduce recurring rates in all population, different age groups and obese patients. The interaction among age, hospitalization delay and drug treatment on SARS-CoV-2 recurring rate is shown in Figure 3 . Interestingly, we found out that the combination of anti-influenza virus drug, oseltamivir, with Interferon/Lopinavir/Ritonavir/Arbidol, has very good outcome (recurring rate of 0.172), supporting the hypothesis of co-infection of influenzas and SARS-CoV-2. . https://doi.org/10.1101/2020.07.29.20164699 doi: medRxiv preprint Supplement Table Table S1 : Clinical characteristics, laboratory findings, treatments, and outcomes of Covid-19 patients with and without recurrence of SARS-CoV-2 PCR positivity during hospitalization.	./cache/cord-260697-oepk0b1d.txt	./txt/cord-260697-oepk0b1d.txt