Natural-Language Processing: Crucible for Computational Theories of Cognition
Abstract
The COVID-19 pandemic has directly impacted integrated substance use and prenatal care delivery in the United States and has driven a rapid transformation from in-person prenatal care to a hybrid telemedicine care model. Additionally, changes in regulations for take home dosing for methadone treatment for opioid use disorder due to COVID-19 have impacted pregnant and postpartum women. We review the literature on prenatal care models and discuss our experience with integrated substance use and prenatal care delivery during COVID-19 at New England's largest safety net hospital and national leader in substance use care. In our patient-centered medical home for pregnant and postpartum patients with substance use disorder, patients' early responses to these changes have been overwhelmingly positive. Should clinicians continue to use these models, thoughtful planning and further research will be necessary to ensure equitable access to the benefits of telemedicine and take home dosing for all pregnant and postpartum patients with substance use disorder.
Cite
Text
Rosenschein. "Natural-Language Processing: Crucible for Computational Theories of Cognition." International Joint Conference on Artificial Intelligence, 1983. doi:10.1016/j.jsat.2020.108273Markdown
[Rosenschein. "Natural-Language Processing: Crucible for Computational Theories of Cognition." International Joint Conference on Artificial Intelligence, 1983.](https://mlanthology.org/ijcai/1983/rosenschein1983ijcai-natural/) doi:10.1016/j.jsat.2020.108273BibTeX
@inproceedings{rosenschein1983ijcai-natural,
title = {{Natural-Language Processing: Crucible for Computational Theories of Cognition}},
author = {Rosenschein, Stanley J.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1983},
pages = {1180-1186},
doi = {10.1016/j.jsat.2020.108273},
url = {https://mlanthology.org/ijcai/1983/rosenschein1983ijcai-natural/}
}