Risk assessment of imported malaria in China
A machine learning perspective
Bibliographic Data
| ID | 15380476 |
|---|---|
| Authors | Shuo Yang (0000-0003-4993-9935, Hospital for Tropical Diseases, corresponding author), Ruoyang Li (0000-0001-8268-4386, Hospital for Tropical Diseases), Ruo-yang Li, Shu-ning Yan (National Institute for Parasitic Diseases), Han-yin Yang (Vector (United States)), Zi-you Cao (Vector (United States)), Li Zhang (0000-0002-4441-5131, National Institute for Parasitic Diseases), Jing-Bo Xue (National Institute for Parasitic Diseases), Zhigui Xia (0000-0002-0569-0368, Hospital for Tropical Diseases), Zhi-Gui Xia, Shang Xia (0000-0003-2290-7335, National Institute for Parasitic Diseases), Bin Zheng (0000-0001-8334-0833, National Institute for Parasitic Diseases) |
| Year | 2024 |
| Volume | 24 |
| Issue | 1 |
| Pages | 865-865 |
| Publication date | 2024-03-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1471-2458 • E-ISSN: 1471-2458 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s12889-024-17929-9 |
| PMID | 38509529 |
| OpenAlex | W4392984837 |
| Language | EN |
| References cited | 37 |
Machine learning algorithms have reliable application prospects in risk assessment of imported malaria in China. This study provides a new methodological reference for the risk assessment and control strategies adjusting of imported malaria in China
Biostatistics · China · Environmental health · Geography · Machine learning · Malaria · Public health · Computer Science · Digital Imaging for Blood Diseases · Malaria Research and Control · Medicine · Viral Infections and Vectors · Artificial Intelligence · Immunology
| Citation velocity | historical |
|---|---|
| Highly cited | No |