The Emerging Role of Artificial Intelligence in the Fight Against COVID-19
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 popu...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ghose, Aruni [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Umfang: |
2 |
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| Übergeordnetes Werk: |
Enthalten in: Phase transition and alternation in a model of perceptual bistability in the presence of Lévy noise - Feng, Jing ELSEVIER, 2018, official organ of the European Association of Urology, the European Organization for Research and Treatment of Cancer - Genito-Urinary Group, the European Society for Urological Oncology and Endocrinology, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:78 ; year:2020 ; number:6 ; pages:775-776 ; extent:2 |
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| DOI / URN: |
10.1016/j.eururo.2020.09.031 |
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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. |
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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. |
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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. |
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