Abstract
The coronavirus disease 2019 (COVID-19) pandemic has generated large volumes of clinical data that can be an invaluable resource towards answering a number of important questions for this and future pandemics. Artificial intelligence can have an important role in analysing such data to identify populations at higher risk of COVID-19–related urological pathologies and to suggest treatments that block viral entry into cells by interrupting the angiotensin-converting enzyme 2-transmembrane serine protease 2 (ACE2-TMPRSS2) pathway.
Original language | English |
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Journal | European Urology |
Early online date | 17 Sept 2020 |
DOIs | |
Publication status | E-pub ahead of print - 17 Sept 2020 |