9 citations · 10 across the 3 of their papers we have counts for
4 papers · 1 filter
Flexible Bayesian Tensor Decomposition for Verbal Autopsy Data
Yu Zhu, Zehang Richard Li
Cause-of-death data is fundamental for understanding population health trends and inequalities as well as designing and evaluating public health interventions. A significant propor…
Verbal Autopsy in Civil Registration and Vital Statistics: The Symptom-Cause Information Archive
Samuel J. Clark, Martin W. Bratschi, Philip Setel +6
The burden of disease is fundamental to understanding, prioritizing, and monitoring public health interventions. Cause of death is required to calculate the burden of disease, but…
Quantifying the Contributions of Training Data and Algorithm Logic to the Performance of Automated Cause-assignment Algorithms for Verbal Autopsy
Samuel J. Clark, Zehang Li, Tyler H. McCormick
A verbal autopsy (VA) consists of a survey with a relative or close contact of a person who has recently died. VA surveys are commonly used to infer likely causes of death for indi…
Bayesian factor models for probabilistic cause of death assessment with verbal autopsies
Tsuyoshi Kunihama, Zehang Richard Li, Samuel J. Clark +1
The distribution of deaths by cause provides crucial information for public health planning, response, and evaluation. About 60% of deaths globally are not registered or given a ca…