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Prospects for automated diagnosis of verbal autopsies

Authors: Michel Garenne; Michel Garenne;

Prospects for automated diagnosis of verbal autopsies

Abstract

Verbal autopsy is a method for assessing probable causes of death from lay reporting of signs, symptoms and circumstances by family members or caregivers of a deceased person. Several methods of automated diagnoses of causes of death from standardized verbal autopsy questionnaires have been developed recently (Inter-VA, Tariff, Random Forest and King-Lu). Their performances have been assessed in a series of papers in BMC Medicine. Overall, and despite high specificity, the current strategies of automated computer diagnoses lead to relatively low sensitivity and positive predictive values, even for causes which are expected to be easily assessed by interview. Some methods have even abnormally low sensitivity for selected diseases of public health importance and could probably be improved. Ways to improve the current strategies are proposed: more detailed questionnaires; using more information on disease duration; stratifying for large groups of causes of death by age, sex and main category; using clusters of signs and symptoms rather than quantitative scores or ranking; separating indeterminate causes; imputing unknown cause with appropriate methods. Please see related articles: http://www.biomedcentral.com/1741-7015/12/5; http://www.biomedcentral.com/1741-7015/12/19; http://www.biomedcentral.com/1741-7015/12/20; http://www.biomedcentral.com/1741-7015/12/21; http://www.biomedcentral.com/1741-7015/12/22; http://www.biomedcentral.com/1741-7015/12/23.

Keywords

Medicine(all), Automation, Laboratory, Public health, 610, Cause of death, Surveys and Questionnaires, 616, Automated diagnosis, Health information system, Evaluation of health programs, Commentary, [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Humans, Verbal autopsy, Autopsy

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Average
Top 10%
Top 10%
Green
gold