Academic Journal
Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data
| العنوان: | Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data |
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| المؤلفون: | Rasmy, Laila, Nigo, Masayuki, Kannadath, Bijun Sai, Xie, Ziqian, Mao, Bingyu, Patel, Khush, Zhou, Yujia, Zhang, Wanheng, Ross, Angela, Xu, Hua, Zhi, Degui |
| المصدر: | The Lancet Digital Health ; volume 4, issue 6, page e415-e425 ; ISSN 2589-7500 |
| بيانات النشر: | Elsevier BV |
| سنة النشر: | 2022 |
| المجموعة: | ScienceDirect (Elsevier - Open Access Articles via Crossref) |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.1016/s2589-7500(22)00049-8 |
| الاتاحة: | http://dx.doi.org/10.1016/s2589-7500(22)00049-8 https://api.elsevier.com/content/article/PII:S2589750022000498?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S2589750022000498?httpAccept=text/plain |
| Rights: | https://www.elsevier.com/tdm/userlicense/1.0/ ; http://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.E7EFFAC9 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/s2589-7500(22)00049-8 |
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