scholarly journals TREC-COVID: rationale and structure of an information retrieval shared task for COVID-19

2020 ◽  
Vol 27 (9) ◽  
pp. 1431-1436 ◽  
Author(s):  
Kirk Roberts ◽  
Tasmeer Alam ◽  
Steven Bedrick ◽  
Dina Demner-Fushman ◽  
Kyle Lo ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Clinical Research ◽  
Data Use ◽  
Iteration Process ◽  
Assessment Process ◽  
Evaluation Metrics ◽  
Test Collection ◽  
Shared Task ◽  
Relevance Criteria ◽  
Research Questions

Abstract TREC-COVID is an information retrieval (IR) shared task initiated to support clinicians and clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal assumptions, which can be seen by examining 9 important basic IR research questions related to pandemic situations. TREC-COVID differs from traditional IR shared task evaluations with special considerations for the expected users, IR modality considerations, topic development, participant requirements, assessment process, relevance criteria, evaluation metrics, iteration process, projected timeline, and the implications of data use as a post-task test collection. This article describes how all these were addressed for the particular requirements of developing IR systems under a pandemic situation. Finally, initial participation numbers are also provided, which demonstrate the tremendous interest the IR community has in this effort.

Report on the 4th Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries at SIGIR 2019

2019 ◽  
Vol 53 (2) ◽  
pp. 3-10
Author(s):  
Muthu Kumar Chandrasekaran ◽  
Philipp Mayr
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Natural Language ◽  
Research And Development ◽  
Language Processing ◽  
Digital Libraries ◽  
State Of The Art ◽  
Shared Task ◽  
Processing Information ◽  
Joint Workshop

The 4 th joint BIRNDL workshop was held at the 42nd ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019) in Paris, France. BIRNDL 2019 intended to stimulate IR researchers and digital library professionals to elaborate on new approaches in natural language processing, information retrieval, scientometrics, and recommendation techniques that can advance the state-of-the-art in scholarly document understanding, analysis, and retrieval at scale. The workshop incorporated different paper sessions and the 5 th edition of the CL-SciSumm Shared Task.

Shared-Task Worklists Improve Clinical Trial Recruitment Workflow in an Academic Emergency Department

2021 ◽  
Vol 12 (02) ◽  
pp. 293-300
Author(s):  
Kevin S. Naceanceno ◽  
Stacey L. House ◽  
Phillip V. Asaro
Keyword(s):  
Clinical Trial ◽  
Emergency Department ◽  
Clinical Trials ◽  
Clinical Research ◽  
Substantial Reduction ◽  
Text Message ◽  
High Volume ◽  
Text Messages ◽  
Shared Task ◽  
Clinical Research Coordinators

Abstract Background Clinical trials performed in our emergency department at Barnes-Jewish Hospital utilize a centralized infrastructure for alerting, screening, and enrollment with rule-based alerts sent to clinical research coordinators. Previously, all alerts were delivered as text messages via dedicated cellular phones. As the number of ongoing clinical trials increased, the volume of alerts grew to an unmanageable level. Therefore, we have changed our primary notification delivery method to study-specific, shared-task worklists integrated with our pre-existing web-based screening documentation system. Objective To evaluate the effects on screening and recruitment workflow of replacing text-message delivery of clinical trial alerts with study-specific shared-task worklists in a high-volume academic emergency department supporting multiple concurrent clinical trials. Methods We analyzed retrospective data on alerting, screening, and enrollment for 10 active clinical trials pre- and postimplementation of shared-task worklists. Results Notifications signaling the presence of potentially eligible subjects for clinical trials were more likely to result in a screen (p < 0.001) with the implementation of shared-task worklists compared with notifications delivered as text messages for 8/10 clinical trials. The change in workflow did not alter the likelihood of a notification resulting in an enrollment (p = 0.473). The Director of Research reported a substantial reduction in the amount of time spent redirecting clinical research coordinator screening activities. Conclusion Shared-task worklists, with the functionalities we have described, offer a viable alternative to delivery of clinical trial alerts via text message directly to clinical research coordinators recruiting for multiple concurrent clinical trials in a high-volume academic emergency department.

scholarly journals Report on the 11th bibliometric-enhanced information retrieval workshop (BIR 2021)

2021 ◽  
Vol 55 (1) ◽  
pp. 1-9
Author(s):  
Ingo Frommholz ◽  
Guillaume Cabanac ◽  
Philipp Mayr ◽  
Suzan Verberne
Keyword(s):  
Information Retrieval ◽  
Lessons Learned ◽  
Future Research ◽  
Research Questions ◽  
Important Branch

The 11th Bibliometric-enhanced Information Retrieval Workshop (BIR 2021) was held online on April 1st, 2021, at ECIR 2021 as a virtual event. The interdisciplinary BIR workshop series aims to bring together researchers from different communities, especially Scientometrics/Bibliometrics and Information Retrieval. We report on the 11th BIR, its invited talks and accepted papers. Lessons learned from BIR 2021 are discussed and potential future research questions identified that position Bibliometric-enhanced IR as an exciting special yet important branch of IR research.

The Social Value of Research and Health Research Priority-Setting

2021 ◽  
Author(s):  
D.M. Wenner
Keyword(s):  
Clinical Research ◽  
Priority Setting ◽  
Health Research ◽  
Human Subjects ◽  
Social Value ◽  
Research Priority ◽  
The Social ◽  
Research Questions ◽  
Social Scientific ◽  
Health Research Priority Setting

This chapter discusses the social value requirement in clinical research and its intersection with health research priority-setting. The social value requirement states that clinical research involving human subjects is only ethical if it has the potential to produce socially valuable knowledge. The chapter discusses various ways to specify both the justification for and the content of the social value requirement. It goes on to consider the implications of various accounts of the content and justification for the requirement for the ethics of health research priority-setting, showing that while some accounts of the requirement are largely silent with respect to how research questions should be prioritized, others entail robust obligations to prioritize research that might benefit particular groups. The chapter also briefly examines potential arguments for something like a social value requirement in other kinds of research, specifically social scientific research.

scholarly journals Matching research design to clinical research questions

2012 ◽  
Vol 33 (1) ◽  
pp. 49 ◽  
Author(s):  
Sadaf Aslam ◽  
Kedar Mehta ◽  
Helen Georgiev ◽  
Ambuj Kumar
Keyword(s):  
Clinical Research ◽  
Research Design ◽  
Research Questions

scholarly journals Estimands: bringing clarity and focus to research questions in clinical trials

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e052953
Author(s):  
Timothy Peter Clark ◽  
Brennan C Kahan ◽  
Alan Phillips ◽  
Ian White ◽  
James R Carpenter
Keyword(s):  
Clinical Trial ◽  
Sensitivity Analysis ◽  
Clinical Trials ◽  
Clinical Research ◽  
Recent Work ◽  
Treatment Effect ◽  
Research Question ◽  
Probability Of Success ◽  
Research Questions

Precise specification of the research question and associated treatment effect of interest is essential in clinical research, yet recent work shows that they are often incompletely specified. The ICH E9 (R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials introduces a framework that supports researchers in precisely and transparently specifying the treatment effect they aim to estimate in their clinical trial. In this paper, we present practical examples to demonstrate to all researchers involved in clinical trials how estimands can help them to specify the research question, lead to a better understanding of the treatment effect to be estimated and hence increase the probability of success of the trial.

Towards a Possibilistic Information Retrieval System Using Semantic Query Expansion

2012 ◽  
pp. 216-242
Author(s):  
Bilel Elayeb ◽  
Ibrahim Bounhas ◽  
Oussama Ben Khiroun ◽  
Fabrice Evrard ◽  
Narjès Bellamine-BenSaoud
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Retrieval System ◽  
Possibility Theory ◽  
Information Retrieval System ◽  
Test Collection ◽  
Expansion Process ◽  
Semantic Query ◽  
Linguistic Resources ◽  
Relevance Measure

This paper presents a new possibilistic information retrieval system using semantic query expansion. The work is involved in query expansion strategies based on external linguistic resources. In this case, the authors exploited the French dictionary “Le Grand Robert”. First, they model the dictionary as a graph and compute similarities between query terms by exploiting the circuits in the graph. Second, the possibility theory is used by taking advantage of a double relevance measure (possibility and necessity) between the articles of the dictionary and query terms. Third, these two approaches are combined by using two different aggregation methods. The authors also benefit from an existing approach for reweighting query terms in the possibilistic matching model to improve the expansion process. In order to assess and compare the approaches, the authors performed experiments on the standard ‘LeMonde94’ test collection.

Automatic Keyword Extraction From Text Documents

2021 ◽  
pp. 71-91
Author(s):  
Furkan Goz ◽  
Alev Mutlu
Keyword(s):  
Information Retrieval ◽  
State Of The Art ◽  
Online News ◽  
Evaluation Metrics ◽  
Keyword Extraction ◽  
Feature Engineering ◽  
Extraction Techniques ◽  
Text Documents ◽  
Scientific Papers ◽  
Benchmark Datasets

Keyword indexing is the problem of assigning keywords to text documents. It is an important task as keywords play crucial roles in several information retrieval tasks. The problem is also challenging as the number of text documents is increasing, and such documents come in different forms (i.e., scientific papers, online news articles, and microblog posts). This chapter provides an overview of keyword indexing and elaborates on keyword extraction techniques. The authors provide the general motivations behind the supervised and the unsupervised keyword extraction and enumerate several pioneering and state-of-the-art techniques. Feature engineering, evaluation metrics, and benchmark datasets used to evaluate the performance of keyword extraction systems are also discussed.

Comments on Bulterman-Bos: Education Research as a Distributed Activity Across Universities

2008 ◽  
Vol 37 (7) ◽  
pp. 424-428 ◽  
Author(s):  
Ellen Condliffe Lagemann
Keyword(s):  
Education Research ◽  
Problem Solving ◽  
Clinical Research ◽  
Research Universities ◽  
Policy Makers ◽  
Problem Finding ◽  
Finding Study ◽  
Research Questions ◽  
Good Research

In response to Bulterman-Bos (2008) , this article discusses three kinds of research needed in education: problem-finding research, which helps frame good research questions; problem-solving research, which helps illuminate educational problems; and translational work, which transforms the findings of research into tools that practitioners and policy makers need. Clinical research is most important as a form of problem-finding study. Although it is best carried on in “ed schools,” other kinds of education research are best done in other faculties. For this reason, education research should be a distributed activity, encouraged across all the faculties of research universities.

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