Name
Title | ||
|---|---|---|
CovidDeep: SARS-CoV-2/COVID-19 Test Based on Wearable Medical Sensors and Efficient Neural Networks |
Abstract | ||
|---|---|---|
The novel coronavirus (SARS-CoV-2) has led to a pandemic. The current testing regime based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been unable to keep up with testing demands, and also suffers from a relatively low positive detection rate in the early stages of the resultant COVID-19 disease. Hence, there is a need for an alternative approach for repeated large-scale ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCE.2021.3130228 | IEEE Transactions on Consumer Electronics |
Keywords | DocType | Volume |
COVID-19,Coronaviruses,Computer architecture,Biomedical monitoring,Training data,Brain modeling,Medical services,Deep learning,Neural networks | Journal | 67 |
Issue | ISSN | Citations |
4 | 0098-3063 | 1 |
PageRank | References | Authors |
0.35 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shayan Hassantabar | 1 | 1 | 1.02 |
| Novati Stefano | 2 | 1 | 0.35 |
| Vishweshwar Ghanakota | 3 | 1 | 0.35 |
| Alessandra Ferrari | 4 | 1 | 0.35 |
| Gregory N. Nicola | 5 | 1 | 0.35 |
| Raffaele Bruno | 6 | 1232 | 90.09 |
| Ignazio R. Marino | 7 | 1 | 0.35 |
| Niraj K. Jha | 8 | 5902 | 467.40 |