Predicting the Utility of Scientific Articles for Emerging Pandemics Using Their Titles and Natural Language Processing.
Journal:
Disaster medicine and public health preparedness
PMID:
38726471
Abstract
OBJECTIVE: Not all scientific publications are equally useful to policy-makers tasked with mitigating the spread and impact of diseases, especially at the start of novel epidemics and pandemics. The urgent need for actionable, evidence-based information is paramount, but the nature of preprint and peer-reviewed articles published during these times is often at odds with such goals. For example, a lack of novel results and a focus on opinions rather than evidence were common in coronavirus disease (COVID-19) publications at the start of the pandemic in 2019. In this work, we seek to automatically judge the utility of these scientific articles, from a public health policy making persepctive, using only their titles.