Improving the Performance of Bio-Entity Name Recognition in Biomedical Literature via the Contextual Cues

2007 ◽  
Vol 4 (7) ◽  
pp. 1426-1431
Author(s):  
Zhihao Yang ◽  
Hongfei Lin ◽  
Yanpeng Li
1997 ◽  
Vol 2 (2) ◽  
pp. 118-124
Author(s):  
Geoffrey Hall

Patients who have undergone several sessions of chemotherapy for cancer will sometimes develop anticipatory nausea and vomiting (ANV), these unpleasant side effects occurring as the patients return to the clinic for a further session of treatment. Pavlov's analysis of learning allows that previously neutral cues, such as those that characterize a given place or context, can become associated with events that occur in that context. ANV could thus constitute an example of a conditioned response elicited by the contextual cues of the clinic. In order to investigate this proposal we have begun an experimental analysis of a parallel case in which laboratory rats are given a nausea-inducing treatment in a novel context. We have developed a robust procedure for assessing the acquisition of context aversion in rats given such training, a procedure that shows promise as a possible animal model of ANV. Theoretical analysis of the conditioning processes involved in the formation of context aversions in animals suggests possible behavioral strategies that might be used in the alleviation of ANV, and we report a preliminary experimental test of one of these.


1966 ◽  
Vol 05 (03) ◽  
pp. 142-146
Author(s):  
A. Kent ◽  
P. J. Vinken

A joint center has been established by the University of Pittsburgh and the Excerpta Medica Foundation. The basic objective of the Center is to seek ways in which the health sciences community may achieve increasingly convenient and economical access to scientific findings. The research center will make use of facilities and resources of both participating institutions. Cooperating from the University of Pittsburgh will be the School of Medicine, the Computation and Data Processing Center, and the Knowledge Availability Systems (KAS) Center. The KAS Center is an interdisciplinary organization engaging in research, operations, and teaching in the information sciences.Excerpta Medica Foundation, which is the largest international medical abstracting service in the world, with offices in Amsterdam, New York, London, Milan, Tokyo and Buenos Aires, will draw on its permanent medical staff of 54 specialists in charge of the 35 abstracting journals and other reference works prepared and published by the Foundation, the 700 eminent clinicians and researchers represented on its International Editorial Boards, and the 6,000 physicians who participate in its abstracting programs throughout the world. Excerpta Medica will also make available to the Center its long experience in the field, as well as its extensive resources of medical information accumulated during the Foundation’s twenty years of existence. These consist of over 1,300,000 English-language _abstract of the world’s biomedical literature, indexes to its abstracting journals, and the microfilm library in which complete original texts of all the 3,000 primary biomedical journals, monitored by Excerpta Medica in Amsterdam are stored since 1960.The objectives of the program of the combined Center include: (1) establishing a firm base of user relevance data; (2) developing improved vocabulary control mechanisms; (3) developing means of determining confidence limits of vocabulary control mechanisms in terms of user relevance data; 4. developing and field testing of new or improved media for providing medical literature to users; 5. developing methods for determining the relationship between learning and relevance in medical information storage and retrieval systems’; and (6) exploring automatic methods for retrospective searching of the specialized indexes of Excerpta Medica.The priority projects to be undertaken by the Center are (1) the investigation of the information needs of medical scientists, and (2) the development of a highly detailed Master List of Biomedical Indexing Terms. Excerpta Medica has already been at work on the latter project for several years.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bo Zhang ◽  
Bingjie Zhang ◽  
Zhulin Zhou ◽  
Yutong Guo ◽  
Dan Wang

AbstractObjectiveGlycosylated hemoglobin (HbA1c) has obvious clinical value in the diagnosis of diabetes, but the conclusions on the diagnostic value of diabetic retinopathy (DR) are not consistent. This study aims to comprehensively evaluate the accuracy of glycosylated hemoglobin in the diagnosis of diabetic retinopathy through the meta-analysis of diagnostic tests.MethodsCochrane Library, Embase, PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), China Wanfang Database, Chinese Biomedical Literature Database (CBM) were searched until November, 2020. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess the quality of the included studies. The pooled sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR) and areas under the receiver operating characteristic (ROC) curve were calculated by Stata 15.0 software.ResultsAfter screening, 18 high-quality papers were included. The results of meta-analysis showed that the combined DOR = 18.19 (95% CI: 10.99–30.11), the sensitivity= 0.81 (95% CI): 0.75 ~ 0.87), specificity = 0.81 (95%CI: 0.72 ~ 0.87), +LR = 4.2 (95%CI: 2.95 ~ 6.00), −LR = 0.23 (95%CI: 0.17 ~ 0.31), and the area under the Summary ROC curve was 0.88 (95%CI:  0.85 ~ 0.90).ConclusionThe overall accuracy of HbA1cC forin diagnosing diabetic retinopathy is good. As it is more stable than blood sugar and is not affected by meals, it may be a suitable indicator for diabetic retinopathy.


Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Carlos-Francisco Méndez-Cruz ◽  
Antonio Blanchet ◽  
Alan Godínez ◽  
Ignacio Arroyo-Fernández ◽  
Socorro Gama-Castro ◽  
...  

Abstract Transcription factors (TFs) play a main role in transcriptional regulation of bacteria, as they regulate transcription of the genetic information encoded in DNA. Thus, the curation of the properties of these regulatory proteins is essential for a better understanding of transcriptional regulation. However, traditional manual curation of article collections to compile descriptions of TF properties takes significant time and effort due to the overwhelming amount of biomedical literature, which increases every day. The development of automatic approaches for knowledge extraction to assist curation is therefore critical. Here, we show an effective approach for knowledge extraction to assist curation of summaries describing bacterial TF properties based on an automatic text summarization strategy. We were able to recover automatically a median 77% of the knowledge contained in manual summaries describing properties of 177 TFs of Escherichia coli K-12 by processing 5961 scientific articles. For 71% of the TFs, our approach extracted new knowledge that can be used to expand manual descriptions. Furthermore, as we trained our predictive model with manual summaries of E. coli, we also generated summaries for 185 TFs of Salmonella enterica serovar Typhimurium from 3498 articles. According to the manual curation of 10 of these Salmonella typhimurium summaries, 96% of their sentences contained relevant knowledge. Our results demonstrate the feasibility to assist manual curation to expand manual summaries with new knowledge automatically extracted and to create new summaries of bacteria for which these curation efforts do not exist. Database URL: The automatic summaries of the TFs of E. coli and Salmonella and the automatic summarizer are available in GitHub (https://github.com/laigen-unam/tf-properties-summarizer.git).


Sign in / Sign up

Export Citation Format

Share Document