Rare Disease Diagnosis as an Information Retrieval Task

Dragusin, Radu; Petcu, Paula; Lioma, Christina; Larsen, Birger; Jørgensen, Henrik; Winther, Ole

doi:10.1007/978-3-642-23318-0_38

Cited by 10 publications

(7 citation statements)

References 2 publications

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“…If, however, strong deviations did arise, we expect that models based on autoregression and queries re-ranked based on correlation with seasonal models will perform much worse. This work complements the use of information retrieval and machine learning methods in the wider area of medical and health informatics [1,2].…”

Section: Resultsmentioning

confidence: 99%

“…Our approach consists of two steps. (1) We model the seasonal variation of ILI activity, and (2) we select queries whose search frequency ts aspects of this seasonality. Speci cally, we present two variations of our algorithm: select queries that correlate with our seasonal model of ILI, and select queries that correlate with the residual between the seasonal model and observed ILI rates.…”

Section: Introductionmentioning

confidence: 99%

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Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation

Hansen

Mølbak

Cox

et al. 2017

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

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In uenza-like illness (ILI) estimation from web search data is an important web analytics task. The basic idea is to use the frequencies of queries in web search logs that are correlated with past ILI activity as features when estimating current ILI activity. It has been noted that since in uenza is seasonal, this approach can lead to spurious correlations with features/queries that also exhibit seasonality, but have no relationship with ILI. Spurious correlations can, in turn, degrade performance. To address this issue, we propose modeling the seasonal variation in ILI activity and selecting queries that are correlated with the residual of the seasonal model and the observed ILI signal. Experimental results show that re-ranking queries obtained by Google Correlate based on their correlation with the residual strongly favours ILI-related queries.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation

Hansen

Mølbak

Cox

et al. 2017

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

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“…This indicates the potential usefulness of web data, such as query frequencies, to predict vaccination uptake in countries where there is no national vaccination registry. This work complements wider efforts in tackling medical and health problems computationally with machine learning or retrieval [20,21].…”

Section: Discussionmentioning

confidence: 78%

Ensemble Learned Vaccination Uptake Prediction using Web Search Queries

Hansen

Lioma

Mølbak

2016

Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

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We present a method that uses ensemble learning to combine clinical and web-mined time-series data in order to predict future vaccination uptake. The clinical data is official vaccination registries, and the web data is query frequencies collected from Google Trends. Experiments with official vaccine records show that our method predicts vaccination uptake effectively (4.7 Root Mean Squared Error). Whereas performance is best when combining clinical and web data, using solely web data yields comparative performance. To our knowledge, this is the first study to predict vaccination uptake using web data (with and without clinical data).

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“…To measure media coverage related to the MMR vaccine, we constructed a query to retrieve relevant news items from the Infomedia archive (this is standard practice when mining health information from the web [18,19]). The query was designed to have high sensitivity, in other words, most relevant news items should be retrieved.…”

Section: Methodsmentioning

confidence: 99%

Relationship Between Media Coverage and Measles-Mumps-Rubella (MMR) Vaccination Uptake in Denmark: Retrospective Study

Hansen¹,

Mølbak²,

Cox³

et al. 2019

JMIR Public Health Surveill

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Background Understanding the influence of media coverage upon vaccination activity is valuable when designing outreach campaigns to increase vaccination uptake. Objective To study the relationship between media coverage and vaccination activity of the measles-mumps-rubella (MMR) vaccine in Denmark. Methods We retrieved data on media coverage (1622 articles), vaccination activity (2 million individual registrations), and incidence of measles for the period 1997-2014. All 1622 news media articles were annotated as being provaccination, antivaccination, or neutral. Seasonal and serial dependencies were removed from the data, after which cross-correlations were analyzed to determine the relationship between the different signals. Results Most (65%) of the anti-vaccination media coverage was observed in the period 1997-2004, immediately before and following the 1998 publication of the falsely claimed link between autism and the MMR vaccine. There was a statistically significant positive correlation between the first MMR vaccine (targeting children aged 15 months) and provaccination media coverage ( r =.49, P =.004) in the period 1998-2004. In this period the first MMR vaccine and neutral media coverage also correlated ( r =.45, P =.003). However, looking at the whole period, 1997-2014, we found no significant correlations between vaccination activity and media coverage. Conclusions Following the falsely claimed link between autism and the MMR vaccine, provaccination and neutral media coverage correlated with vaccination activity. This correlation was only observed during a period of controversy which indicates that the population is more susceptible to media influence when presented with diverging opinions. Additionally, our findings suggest that the influence of media is stronger on parents when they are deciding on the first vaccine of their children, than on the subsequent vaccine because correlations were only found for the first MMR vaccine.

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Rare Disease Diagnosis as an Information Retrieval Task

Cited by 10 publications

References 2 publications

Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation

Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation

Ensemble Learned Vaccination Uptake Prediction using Web Search Queries

Relationship Between Media Coverage and Measles-Mumps-Rubella (MMR) Vaccination Uptake in Denmark: Retrospective Study

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