The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Timeline
Mendeley readers
| Title |
Using machine learning models to predict the duration of the recovery of COVID-19 patients hospitalized in Fangcang shelter hospital during the Omicron BA. 2.2 pandemic
|
|---|---|
| Published in |
Frontiers in Medicine, November 2022
|
| DOI | 10.3389/fmed.2022.1001801 |
| Pubmed ID | |
| Authors |
Yu Xu, Wei Ye, Qiuyue Song, Linlin Shen, Yu Liu, Yuhang Guo, Gang Liu, Hongmei Wu, Xia Wang, Xiaorong Sun, Li Bai, Chunmei Luo, Tongquan Liao, Hao Chen, Caiping Song, Chunji Huang, Yazhou Wu, Zhi Xu |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 18% |
| Student > Ph. D. Student | 1 | 9% |
| Lecturer | 1 | 9% |
| Student > Postgraduate | 1 | 9% |
| Unknown | 6 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 2 | 18% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Medicine and Dentistry | 1 | 9% |
| Unknown | 6 | 55% |