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

Variation among Australian isolates of Colletotrichum acutatum, the almond anthracnose pathogen

http://www.isppweb.org/foodsecurity_mins1023.as

Sampling and Definitions of Placental Lesions: Amsterdam Placental Workshop Group Consensus Statement

Context.-The value of placental examination in investigations of adverse pregnancy outcomes may be compromised by sampling and definition differences between laboratories. Objective.-To establish an agreed-upon protocol for sampling the placenta, and for diagnostic criteria for placental lesions. Recommendations would cover reporting placentas in tertiary centers as well as in community hospitals and district general hospitals, and are also relevant to the scientific research community. Data Sources.-Areas of controversy or uncertainty were explored prior to a 1-day meeting where placental and perinatal pathologists, and maternal-fetal medicine specialists discussed available evidence and subsequently reached consensus where possible. Conclusions.-The group agreed on sets of uniform sampling criteria, placental gross descriptors, pathologic terminologies, and diagnostic criteria. The terminology and microscopic descriptions for maternal vascular malperfusion, fetal vascular malperfusion, delayed villous maturation, patterns of ascending intrauterine infection, and villitis of unknown etiology were agreed upon. Topics requiring further discussion were highlighted. Ongoing developments in our understanding of the pathology of the placenta, scientific bases of the maternofetoplacental triad, and evolution of the clinical significance of defined lesions may necessitate further refinements of these consensus guidelines. The proposed structure will assist in international comparability of clinicopathologic and scientific studies and assist in refining the significance of lesions associated with adverse pregnancy and later health outcomes

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