Improving Systematic Review Creation With Information Retrieval

2018 ◽  
Author(s):  
Harrisen Scells
Keyword(s):  
Systematic Review ◽  
Information Retrieval

scholarly journals The Online Health Information Needs of Family Physicians: Systematic Review of Qualitative and Quantitative Studies (Preprint)

2020 ◽  
Author(s):  
Piet van der Keylen ◽  
Johanna Tomandl ◽  
Katharina Wollmann ◽  
Ralph Möhler ◽  
Mario Sofroniou ◽  
...  
Keyword(s):  
Systematic Review ◽  
Information Retrieval ◽  
Health Information ◽  
Full Text ◽  
Information Needs ◽  
Family Physicians ◽  
Online Health Information ◽  
Online Information ◽  
Qualitative And Quantitative ◽  
Quantitative Studies

BACKGROUND Digitalization and the increasing availability of online information have changed the way in which information is searched for and retrieved by the public and by health professionals. The technical developments in the last two decades have transformed the methods of information retrieval. Although systematic evidence exists on the general information needs of specialists, and in particular, family physicians (FPs), there have been no recent systematic reviews to specifically address the needs of FPs and any barriers that may exist to accessing online health information. OBJECTIVE This review aims to provide an up-to-date perspective on the needs of FPs in searching, retrieving, and using online information. METHODS This systematic review of qualitative and quantitative studies searched a multitude of databases spanning the years 2000 to 2020 (search date January 2020). Studies that analyzed the online information needs of FPs, any barriers to the accessibility of information, and their information-seeking behaviors were included. Two researchers independently scrutinized titles and abstracts, analyzing full-text papers for their eligibility, the studies therein, and the data obtained from them. RESULTS The initial search yielded 4541 studies for initial title and abstract screening. Of the 144 studies that were found to be eligible for full-text screening, 41 were finally included. A total of 20 themes were developed and summarized into 5 main categories: <i>individual needs</i> of FPs before the search; <i>access needs</i>, including factors that would facilitate or hinder information retrieval; <i>quality needs</i> of the information to hand; <i>utilization needs</i> of the information available; and <i>implication needs</i> for everyday practice. CONCLUSIONS This review suggests that searching, accessing, and using online information, as well as any pre-existing needs, barriers, or demands, should not be perceived as separate entities but rather be regarded as a sequential process. Apart from accessing information and evaluating its quality, FPs expressed concerns regarding the applicability of this information to their everyday practice and its subsequent relevance to patient care. Future online information resources should cater to the needs of the primary care setting and seek to address the way in which such resources may be adapted to these specific requirements.

UcEF for Semantic IR

2021 ◽  
pp. 190-217
Author(s):  
Bernard Ijesunor Akhigbe
Keyword(s):  
Systematic Review ◽  
Information Retrieval ◽  
Information Needs ◽  
Semantic Search ◽  
Related Data ◽  
Multiple Contexts ◽  
Descriptive Approach ◽  
The Impact ◽  
Cognitive User ◽  
Data Analytic

At present, keyword-based techniques allow information retrieval (IR) but are unable to capture the conceptualizations in users' information needs and contents. The response to this has been semantic search computing with commendable success. Surprisingly, it is still difficult to evaluate Semantic IR (SIR) and understand the user contexts. The absence of a standardized cognitive user-centred evaluative paradigm (CUcEP) further exacerbates these challenges. This chapter provides the state-of-the-art on IR and SIR evaluation and a systematic review of contexts. Appropriate user-centred theories and the proposed evaluative framework with its integrated-context, web analytic conception, and related data analytic technique are presented. A descriptive approach is adopted, with the conclusion that multiple contexts are essential in SIR evaluation since “searching by meaning” is a multi-dimensional cognitive conception, hence the need to consider the impact of context dynamicity. Finally, the foregrounded semantic items will be applied to standardize the CUcEP in future.

scholarly journals The Online Health Information Needs of Family Physicians: Systematic Review of Qualitative and Quantitative Studies

10.2196/18816 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e18816
Author(s):  
Piet van der Keylen ◽  
Johanna Tomandl ◽  
Katharina Wollmann ◽  
Ralph Möhler ◽  
Mario Sofroniou ◽  
...  
Keyword(s):  
Systematic Review ◽  
Information Retrieval ◽  
Health Information ◽  
Full Text ◽  
Information Needs ◽  
Family Physicians ◽  
Online Health Information ◽  
Online Information ◽  
Qualitative And Quantitative ◽  
Quantitative Studies

Background Digitalization and the increasing availability of online information have changed the way in which information is searched for and retrieved by the public and by health professionals. The technical developments in the last two decades have transformed the methods of information retrieval. Although systematic evidence exists on the general information needs of specialists, and in particular, family physicians (FPs), there have been no recent systematic reviews to specifically address the needs of FPs and any barriers that may exist to accessing online health information. Objective This review aims to provide an up-to-date perspective on the needs of FPs in searching, retrieving, and using online information. Methods This systematic review of qualitative and quantitative studies searched a multitude of databases spanning the years 2000 to 2020 (search date January 2020). Studies that analyzed the online information needs of FPs, any barriers to the accessibility of information, and their information-seeking behaviors were included. Two researchers independently scrutinized titles and abstracts, analyzing full-text papers for their eligibility, the studies therein, and the data obtained from them. Results The initial search yielded 4541 studies for initial title and abstract screening. Of the 144 studies that were found to be eligible for full-text screening, 41 were finally included. A total of 20 themes were developed and summarized into 5 main categories: individual needs of FPs before the search; access needs, including factors that would facilitate or hinder information retrieval; quality needs of the information to hand; utilization needs of the information available; and implication needs for everyday practice. Conclusions This review suggests that searching, accessing, and using online information, as well as any pre-existing needs, barriers, or demands, should not be perceived as separate entities but rather be regarded as a sequential process. Apart from accessing information and evaluating its quality, FPs expressed concerns regarding the applicability of this information to their everyday practice and its subsequent relevance to patient care. Future online information resources should cater to the needs of the primary care setting and seek to address the way in which such resources may be adapted to these specific requirements.

Gathering Data: Searching Literature and Selection Criteria

2013 ◽  
Author(s):  
Isabelle M. Côté ◽  
Peter S. Curtis ◽  
Hannah R. Rothstein ◽  
Gavin B. Stewart
Keyword(s):  
Systematic Review ◽  
Information Retrieval ◽  
Selection Criteria ◽  
Meta Analysis ◽  
Inclusion Criteria ◽  
Literature Searching ◽  
Scoping Study ◽  
Study Selection ◽  
Important Relationship ◽  
Gathering Data

There is an important relationship between how thorough and unbiased the search for relevant data is and the validity of the resulting meta-analysis. Many reviewers fail to uncover citations to documents relevant to their project because of inadequate search tools or strategies. This chapter covers literature searching and information retrieval, as well as the application of study selection (inclusion) criteria. Best practices include carrying out an initial scoping study to assess how much literature is available and whether a systematic review and meta-analysis are possible; developing an explicit search protocol which details exactly how you will go about searching the literature; and outlining clear study selection criteria so that the reasons for inclusion or exclusion of studies are transparent.

scholarly journals UMLS at 30 years, how is it used and published?---A systematic review (Preprint)

2020 ◽  
Author(s):  
Xia Jing
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Data Mining ◽  
Medical Education ◽  
Information Retrieval ◽  
Patient Care ◽  
Knowledge Discovery ◽  
Digital Library ◽  
Digital Libraries ◽  
English Language

BACKGROUND Background: The unified medical language system (UMLS) has been a critical tool in biomedical and health informatics, and the year 2020 marks the 30th anniversary of UMLS. Despite its longevity, there is no systematic review on UMLS, in general. Thus, this systematic review was conducted to provide an overview of UMLS and its usage in English-language publications in the last 30 years. OBJECTIVE Objectives: The objective is twofold: to provide a comprehensive and systematic picture of the themes, their subtopics, and the publications under each category and to document systematic evidence of UMLS and how it has been used in English-language publications in the last 30 years. METHODS Methods: PubMed, ACM Digital Library, and Nursing & Allied Health Database were used to search for literature. The primary literature search strategy was as follows: UMLS was used as a MeSH term or a keyword or appeared in the title or abstract. Only English-language publications were considered. RESULTS Results: A total of 943 publications were included in the final analysis. After analysis and categorization of publications, UMLS was found to be used in the following emerging themes: natural language processing (NLP) (230 publications), information retrieval (125 publications), terminology study (90 publications), ontology and modeling (80 publications), medical subdomains (76 publications), other language studies (53 publications), artificial intelligence tools and applications (46 publications), patient care (35 publications), data mining and knowledge discovery (25 publications), medical education (20 publications), degree-related theses (13 publications), and digital library (5 publications) as well as UMLS itself (150 publications). CONCLUSIONS Conclusions: UMLS has been used and published successfully in patient care, medical education, digital libraries, and software development, as originally planned, as well as in degree-related theses, building artificial intelligence tools, data mining and knowledge discovery and more foundational work in methodology and middle layers that may lead to advanced products. NLP, UMLS itself, and information retrieval are the three themes with the most publications. The review provides systematic evidence of UMLS in English-language peer-reviewed publications in the last 30 years.

scholarly journals Information Retrieval Metrics for Speech Based Systems: A Systematic Review

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Micheal Adenibuyan ◽  
Oluwatoyin Enikuomehin ◽  
Benjamin Aribisala
Keyword(s):  
Systematic Review ◽  
Information Retrieval ◽  
Linear Relationship ◽  
Relevant Information ◽  
Text Search ◽  
Average Precision ◽  
Exclusion Criteria ◽  
Transcription Error ◽  
The Difference ◽  
The Voice

Information Retrieval (IR) allows the identification of relevant information from connected repositories, however their performance have been of research interest leading to investigations in the modalities by which the accuracy of the retrievals are evaluated. Metrics such as Precision, Recall, F-score among others are used to evaluate an IR system. IR use same form of evaluation for both speech and text based system while failing to realize the difference that could have occurred in the process of transcription, especially in the voice to text search, which is the most common speech based search paradigm. This is forming a new set of concerns. This research aim to review and identify the strengths and weaknesses of existing metrics for measuring the performances of speech based. A total of 179 articles were retrieved using Google Scholar repository and were manually examined. Only 25 articles were selected for analysis in this study after applying our predefined inclusion and exclusion criteria. Result shows that Mean Average Precision is the most frequently used metric for speech based IR system with result range from 0.4191 to 0.620. Also transcription error of spoken query or spoken document has a near linear relationship to IR performance. This systematic review serves as a bibliography of speech based IR systems and can be used by those new to the field of IR.

scholarly journals Day-to-day discovery of preprint–publication links

2021 ◽  
Author(s):  
Guillaume Cabanac ◽  
Theodora Oikonomidi ◽  
Isabelle Boutron
Keyword(s):  
Systematic Review ◽  
Information Retrieval ◽  
International Collaboration ◽  
Web Page ◽  
Retrieval Task ◽  
Reference Set ◽  
Published Evidence ◽  
Health Related ◽  
Supplementary Material ◽  
Increase In Accuracy

AbstractPreprints promote the open and fast communication of non-peer reviewed work. Once a preprint is published in a peer-reviewed venue, the preprint server updates its web page: a prominent hyperlink leading to the newly published work is added. Linking preprints to publications is of utmost importance as it provides readers with the latest version of a now certified work. Yet leading preprint servers fail to identify all existing preprint–publication links. This limitation calls for a more thorough approach to this critical information retrieval task: overlooking published evidence translates into partial and even inaccurate systematic reviews on health-related issues, for instance. We designed an algorithm leveraging the Crossref public and free source of bibliographic metadata to comb the literature for preprint–publication links. We tested it on a reference preprint set identified and curated for a living systematic review on interventions for preventing and treating COVID-19 performed by international collaboration: the COVID-NMA initiative (covid-nma.com). The reference set comprised 343 preprints, 121 of which appeared as a publication in a peer-reviewed journal. While the preprint servers identified 39.7% of the preprint–publication links, our linker identified 90.9% of the expected links with no clues taken from the preprint servers. The accuracy of the proposed linker is 91.5% on this reference set, with 90.9% sensitivity and 91.9% specificity. This is a 16.26% increase in accuracy compared to that of preprint servers. We release this software as supplementary material to foster its integration into preprint servers’ workflows and enhance a daily preprint–publication chase that is useful to all readers, including systematic reviewers. This preprint–publication linker currently provides day-to-day updates to the biomedical experts of the COVID-NMA initiative.

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