HIGHLIGHTS
- who: Dian Kesumapramudya Nurputra from the Published in partnership with Seoul National University Bundang Hospital have published the research work: Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition, in the Journal: (JOURNAL)
- what: The focus of the next analysis was to use supervised machine_learning models of LDA, SVM, MLP, and DNN. The studies showed no significant difference in the detected sensor signal patterns of patients with comorbidities compared to those without comorbidities. Essentially, the calculated performance values in the study show the reliability of the DNN algorithm . . .
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