The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine
Open accessAbstract
We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone–based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.
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Citations
Cites
Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence
Liang, H., Tsui, B. Y., Ni, H., Valentim, C. C. S., Baxter, S. L., Liu, G., Cai, W., Kermany, D. S., Sun, X., Chen, J., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0335-9 · Cited by 659
Arabasadi, Z., Alizadehsani, R., Roshanzamir, M., Moosaei, H., & Yarifard, A. A. (2017) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2017.01.004 · Cited by 499
Community Health Workers and Mobile Technology: A Systematic Review of the Literature
Braun, R., Catalani, C., Wimbush, J., & Israelski, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065772 · Cited by 493
Rajalakshmi, R., Subashini, R., Anjana, R. M., & Mohan, V. (2018) · Eye · doi:10.1038/s41433-018-0064-9 · Cited by 462
The use of mobile phones as a data collection tool: A report from a household survey in South Africa
Tomlinson, M., Solomon, W., Singh, Y., Doherty, T., Chopra, M., Ijumba, P., Tsai, A. C., & Jackson, D. (2009) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-9-51 · Cited by 340
Mobile health use in low- and high-income countries: an overview of the peer-reviewed literature
Bastawrous, A., & Armstrong, M. J. (2013) · Journal of the Royal Society of Medicine · doi:10.1177/0141076812472620 · Cited by 236
Short Fabic, M., Choi, Y., & Bird, S. (2012) · Bulletin of the World Health Organization · doi:10.2471/blt.11.095513 · Cited by 198
Paolotti, D., Carnahan, A., Colizza, V., Eames, K., Edmunds, J., Gomes, G., Koppeschaar, C., Rehn, M., Smallenburg, R., Turbelin, C., et al. (2014) · Clinical Microbiology and Infection · doi:10.1111/1469-0691.12477 · Cited by 177
Using artificial intelligence to improve hospital inpatient care
Neill, D. B. (2013) · IEEE Intelligent Systems · doi:10.1109/mis.2013.51 · Cited by 177
Dermatological disease detection using image processing and machine learning
Kumar, V. B., Kumar, S. S., & Saboo, V. (2016) · doi:10.1109/icaipr.2016.7585217 · Cited by 158
Cited by
Pham, Q.-V., Nguyen, D. C., Huynh-The, T., Hwang, W.-J., & Pathirana, P. N. (2020) · IEEE Access · doi:10.1109/access.2020.3009328 · Cited by 413
Blockchain and Artificial Intelligence Technology in E-Health
Tagde, P., Tagde, S., Bhattacharya, T., Tagde, P., Chopra, H., Akter, R., Kaushik, D., & Rahman, M. H. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-16223-0 · Cited by 281
Applications of artificial intelligence in battling against covid-19: A literature review
Tayarani N., M.-H. (2021) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2020.110338 · Cited by 210
Robotics and artificial intelligence in healthcare during COVID-19 pandemic: a systematic review
Sarker, S., Jamal, L., Ahmed, S. F., & Irtisam, N. (2021) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2021.103902 · Cited by 199
Ye, J. (2020) · JMIR Medical Informatics · doi:10.2196/19866 · Cited by 194
Metadata
- Authors
- Srinivasa Rao, A. S. R., & Vazquez, J. A.
- Venue
- Infection Control & Hospital Epidemiology
- Publisher
- Cambridge University Press (CUP)
- Published
- 2020-03-03
- Volume
- 41
- Issue
- 7
- Pages
- 826-830
- ISSN
- 0899-823X (ISSN-L)
- 1559-6834
- OpenAlex
- W3022885394
- Cited by
- 394
- References
- 12
- FWCI
- 55.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- CoChat. (2026). Citation check: Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine. https://app.cochat.ai/papers/10.1017/ice.2020.61
- The paper
- Srinivasa Rao, A. S. R., & Vazquez, J. A. (2020). Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone–based survey when cities and towns are under quarantine. Infection Control & Hospital Epidemiology. https://doi.org/10.1017/ice.2020.61
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
