Open partial horizontal laryngectomies: a proposal for classification by the Working Committee on Nomenclature of the European Laryngological Society.

We present herein the proposal of the European Laryngological Society working committee on nomenclature for a systematic classification of open partial horizontal laryngectomies (OPHL). This is based on the cranio-caudal extent of laryngeal structures resected, instead of a number of different and heterogeneous variables present in existing nomenclatures, usually referring to eponyms, types of pexy, or inferior limit of resection. According to the proposed classification system, we have defined three types of OPHLs: Type I (formerly defined horizontal supraglottic laryngectomy), Type II (previously called supracricoid laryngectomy), and Type III (also named supratracheal laryngectomy). Use of suffixes "a" and "b" in Type II and III OPHLs reflects sparing or not of the suprahyoid epiglottis. Various extensions to one arytenoid, base of tongue, piriform sinus, and crico-arytenoid unit are indicated by abbreviations (ARY, BOT, PIR, and CAU, respectively). Our proposal is not intended to give a comprehensive algorithm of application of different OPHLs to specific clinical situations, but to serve as the basis for obtaining a common language among the head and neck surgical community. We therefore intend to present this classification system as a simple and intuitive teaching instrument, and a tool to be able to compare surgical series with each other and with non-surgical data

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