32 research outputs found

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

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    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

    Supply and demand for liver transplant surgery: Are we training enough surgeons?

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    The purpose of our study is to determine whether the current level of transplant fellow training is sufficient to meet the future demand for liver transplantation in the United States. Historical data from the Nationwide Inpatient Samples (NIS) for the years 1998 through 2003 were used to construct an estimate of the annual number of liver transplant procedures currently being performed in the United States, and the number projected for each year through 2020. Estimates for the current and future number of surgeons performing liver transplant procedures were also constructed using the same database. The NIS database was used because current national transplant registries do not include information on the number of surgeons performing liver transplant procedures. Using historical data derived from the NIS database, we project that the estimated number of liver transplant procedures per surgeon will remain relatively stable through 2020, with each surgeon performing an average of 12.9 procedures in 2020 compared to 12.9 currently. We conclude that the relationship between demand for liver transplantation in the United States and the supply of liver transplant surgeons will remain stable over the next 15 years
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