Proposing Causal Sequence of Death by Neural Machine Translation in Public Health Informatics.

ABSTRACT: Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United States. Timely, accurate and complete death reporting is critical for public health, especially during the COVID-19 pandemic, as institutions and government agencies rely on death reports to formulate responses to communicable diseases. Unfortunately, determining the causes of death is challenging even for experienced physicians. The novel coronavirus and its variants may further complicate the task, as physicians and experts are still investigating COVID-related complications. To assist physicians in accurately reporting causes of death, an advanced Artificial Intelligence (AI) approach is presented to determine a chronically ordered sequence of conditions that lead to death (named as the causal se

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC9452006 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature