Specialized tools are needed when searching the web for rare disease diagnoses

Dragusin, Radu; Petcu, Paula; Lioma, Christina; Larsen, Birger; Jørgensen, Henrik L.; Cox, Ingemar J.; Hansen, Lars Kai; Ingwersen, Peter; Winther, Ole

doi:10.4161/rdis.25001

Cited by 16 publications

(10 citation statements)

References 3 publications

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“…While researchers currently use generic search engines such as Google, DataMed is intended to aggregate metadata across multiple repositories to provide both broad coverage and effective data-specific retrieval tools, accelerating researchers’ exploration of and exposure to potentially relevant data. 21 The DATS model was implemented as a common metadata standard to address the disparity of metadata across repositories. Information retrieval techniques were applied to address the variability in terminology and provide an efficient user interface.…”

Section: Resultsmentioning

confidence: 99%

User needs analysis and usability assessment of DataMed – a biomedical data discovery index

Dixit

Rogith

Narayana

et al. 2017

Journal of the American Medical Informatics Association

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While available data and researchers' information needs are complex and heterogeneous, a successful DDI must meet those needs and fit into the processes of biomedical researchers. Research directions include formalizing researchers' information needs, standardizing overviews of data to facilitate relevance judgments, implementing user interfaces for concept-based searching, and developing evaluation methods for open-ended discovery systems such as DDIs.

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Section: Resultsmentioning

confidence: 99%

User needs analysis and usability assessment of DataMed – a biomedical data discovery index

Dixit

Rogith

Narayana

et al. 2017

Journal of the American Medical Informatics Association

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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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“…However, Beegle is broad-based and lacks focus on rare disease associations. Previous studies have suggested that use of a rare disease-centric corpus as well as specialized search are better than more generic databases and search tools in rare disease diagnosis [11,12]. The potential of using text-mining of disease-phenotype associations from clinical case reports as a means of improving the performance of phenotype-driven differential-diagnosis systems for rare diseases has been reported [13].…”

Section: Introductionmentioning

confidence: 99%

PRIORI-T: A tool for rare disease gene prioritization using MEDLINE

et al. 2020

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Introduction Phenotype-driven rare disease gene prioritization relies on high quality curated resources containing disease, gene and phenotype annotations. However, the effectiveness of gene prioritization tools is constrained by the incomplete coverage of rare disease, phenotype and gene annotations in such curated resources. Methods We extracted rare disease correlation pairs involving diseases, phenotypes and genes from MEDLINE abstracts and used the information propagation algorithm GCAS to build an association network. We built a tool called PRIORI-T for rare disease gene prioritization that uses this network for phenotype-driven rare disease gene prioritization. The quality of disease-gene associations in PRIORI-T was compared with resources such as DisGeNET and Open Targets in the context of rare diseases. The gene prioritization performance of PRI-ORI-T was evaluated using phenotype descriptions of 230 real-world rare disease clinical cases collated from recent publications, as well as compared to other gene prioritization tools such as HANRD and Orphamizer. Results PRIORI-T contains qualitatively better associations than DisGeNET and Open Targets. Furthermore, the causal genes were captured within Top-50 for more than 40% of the realworld clinical cases and within Top-300 for more than 72% of the cases when PRIORI-T was used for gene prioritization. It outperformed other gene prioritization tools such as HANRD and Orphamizer that primarily rely on curated resources. Conclusions PRIORI-T exhibited improved gene prioritization performance without requiring high quality curated data. Thus, it holds great promise in phenotype-driven gene prioritization for rare disease studies.

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Specialized tools are needed when searching the web for rare disease diagnoses

Cited by 16 publications

References 3 publications

User needs analysis and usability assessment of DataMed – a biomedical data discovery index

User needs analysis and usability assessment of DataMed – a biomedical data discovery index

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

PRIORI-T: A tool for rare disease gene prioritization using MEDLINE

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