Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Caenorhabditis elegans: Determining the relationship between srf-6 and nsy-1 in C. elegans

A major component contributing to the ability of nematodes to survive in a diversity of environments may be their ability to alter their surface antigen composition. In doing this, free-living nematodes may be able to avoid pathogenic microbial infections and parasitic nematodes may be able to avoid host’s immune response, both of which rely on recognizable antigens and epitopes located in glycoproteins on the surface of the worm. Two genes, srf-6 and nsy-1, have been shown to affect surface antigen presentation and prior evidence suggests that they are the same gene. This MQP aims to employ complementation tests to investigate whether srf-6 and nsy-1 mutations affect the same genetic function

Freestanding Emergency Department - A Stakeholder Study: Exploring the Feasibility of Freestanding Emergency - Departments in Ware, Massachusetts

The main purpose of this project was to determine the feasibility of establishing a UMass Memorial Medical Center (UMMC)-operated Freestanding Emergency Department (FED) in the town of Ware, MA. Ware and surrounding communities lack access to emergency care, which puts citizens at risk when significant medical care is required in a timely fashion. Baystate Mary Lane Hospital in Ware made the decision to close its inpatient facility in September, 2016. The proposed closure of the emergency department in two years is of significant concern to the residents in the area. It was concluded that FEDs were the best alternative to provide sufficient and cost-effective emergency medical care analogous to that provided by hospitals to the residents of west-central Massachusetts

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press