scholarly journals Trialstreamer: a living, automatically updated database of clinical trial reports

2020 ◽  
Author(s):  
Iain J Marshall ◽  
Benjamin Nye ◽  
Joël Kuiper ◽  
Anna Noel-Storr ◽  
Rachel Marshall ◽  
...  
Keyword(s):  
Automated System ◽  
Free Text ◽  
Gold Standard Method ◽  
Rule Based ◽  
Randomized Controlled ◽  
Structured Information ◽  
Combine Machine ◽  
Clinical Queries ◽  
Clinical Trials Registry ◽  
Extract Information

Objective Randomized controlled trials (RCTs) are the gold standard method for evaluating whether a treatment works in healthcare, but can be difficult to find and make use of. We describe the development and evaluation of a system to automatically find and categorize all new RCT reports. Materials and Methods Trialstreamer, continuously monitors PubMed and the WHO International Clinical Trials Registry Platform (ICTRP), looking for new RCTs in humans using a validated classifier. We combine machine learning and rule-based methods to extract information from the RCT abstracts, including free-text descriptions of trial populations, interventions and outcomes (the 'PICO') and map these snippets to normalised MeSH vocabulary terms. We additionally identify sample sizes, predict the risk of bias, and extract text conveying key findings. We store all extracted data in a database which we make freely available for download, and via a search portal, which allows users to enter structured clinical queries. Results are ranked automatically to prioritize larger and higher-quality studies. Results As of May 2020, we have indexed 669,895 publications of RCTs, of which 18,485 were published in the first four months of 2020 (144/day). We additionally include 303,319 trial registrations from ICTRP. The median trial sample size in the RCTs was 66. Conclusions We present an automated system for finding and categorising RCTs. This yields a novel resource: A database of structured information automatically extracted for all published RCTs in humans. We make daily updates of this database available on our website (trialstreamer.robotreviewer.net).

scholarly journals Trialstreamer: A living, automatically updated database of clinical trial reports

2020 ◽  
Vol 27 (12) ◽  
pp. 1903-1912 ◽  
Author(s):  
Iain J Marshall ◽  
Benjamin Nye ◽  
Joël Kuiper ◽  
Anna Noel-Storr ◽  
Rachel Marshall ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Automated System ◽  
World Health ◽  
Free Text ◽  
Medical Subject Headings ◽  
Gold Standard Method ◽  
Structured Information ◽  
Health Organization ◽  
Clinical Queries ◽  
Clinical Trials Registry

Abstract Objective Randomized controlled trials (RCTs) are the gold standard method for evaluating whether a treatment works in health care but can be difficult to find and make use of. We describe the development and evaluation of a system to automatically find and categorize all new RCT reports. Materials and Methods Trialstreamer continuously monitors PubMed and the World Health Organization International Clinical Trials Registry Platform, looking for new RCTs in humans using a validated classifier. We combine machine learning and rule-based methods to extract information from the RCT abstracts, including free-text descriptions of trial PICO (populations, interventions/comparators, and outcomes) elements and map these snippets to normalized MeSH (Medical Subject Headings) vocabulary terms. We additionally identify sample sizes, predict the risk of bias, and extract text conveying key findings. We store all extracted data in a database, which we make freely available for download, and via a search portal, which allows users to enter structured clinical queries. Results are ranked automatically to prioritize larger and higher-quality studies. Results As of early June 2020, we have indexed 673 191 publications of RCTs, of which 22 363 were published in the first 5 months of 2020 (142 per day). We additionally include 304 111 trial registrations from the International Clinical Trials Registry Platform. The median trial sample size was 66. Conclusions We present an automated system for finding and categorizing RCTs. This yields a novel resource: a database of structured information automatically extracted for all published RCTs in humans. We make daily updates of this database available on our website (https://trialstreamer.robotreviewer.net).

scholarly journals Comparing a Mobile Phone Automated System With a Paper and Email Data Collection System: Substudy Within a Randomized Controlled Trial (Preprint)

2019 ◽  
Author(s):  
Diana M Bond ◽  
Jeremy Hammond ◽  
Antonia W Shand ◽  
Natasha Nassar
Keyword(s):  
Randomized Controlled Trial ◽  
Data Collection ◽  
Cost Analysis ◽  
Mobile Phone ◽  
Response Rate ◽  
Controlled Trial ◽  
Treatment Compliance ◽  
Automated System ◽  
Collection System ◽  
Randomized Controlled

BACKGROUND Traditional data collection methods using paper and email are increasingly being replaced by data collection using mobile phones, although there is limited evidence evaluating the impact of mobile phone technology as part of an automated research management system on data collection and health outcomes. OBJECTIVE The aim of this study is to compare a web-based mobile phone automated system (MPAS) with a more traditional delivery and data collection system combining paper and email data collection (PEDC) in a cohort of breastfeeding women. METHODS We conducted a substudy of a randomized controlled trial in Sydney, Australia, which included women with uncomplicated term births who intended to breastfeed. Women were recruited within 72 hours of giving birth. A quasi-randomized number of women were recruited using the PEDC system, and the remainder were recruited using the MPAS. The outcomes assessed included the effectiveness of data collection, impact on study outcomes, response rate, acceptability, and cost analysis between the MPAS and PEDC methods. RESULTS Women were recruited between April 2015 and December 2016. The analysis included 555 women: 471 using the MPAS and 84 using the PEDC. There were no differences in clinical outcomes between the 2 groups. At the end of the 8-week treatment phase, the MPAS group showed an increased response rate compared with the PEDC group (56% vs 37%; <i>P</i>&lt;.001), which was also seen at the 2-, 6-, and 12-month follow-ups. At the 2-month follow-up, the MPAS participants also showed an increased rate of self-reported treatment compliance (70% vs 56%; <i>P</i>&lt;.001) and a higher recommendation rate for future use (95% vs 64%; <i>P</i>&lt;.001) as compared with the PEDC group. The cost analysis between the 2 groups was comparable. CONCLUSIONS MPAS is an effective and acceptable method for improving the overall management, treatment compliance, and methodological quality of clinical research to ensure the validity and reliability of findings.

scholarly journals MOLES3: Implementing an ISO standards driven data catalogue

2015 ◽  
Vol 10 (1) ◽  
pp. 249-259 ◽  
Author(s):  
Graham A Parton ◽  
Steven Donegan ◽  
Stephen Pascoe ◽  
Ag Stephens ◽  
Spiros Ventouras ◽  
...  
Keyword(s):  
Information Structure ◽  
Information Infrastructure ◽  
Lessons Learned ◽  
Environmental Data ◽  
Data Provenance ◽  
Free Text ◽  
Early Assessment ◽  
Structured Information ◽  
Management Functions ◽  
Previous Iteration

ISO19156 Observations and Measurements (O&M) provides a standardised framework for organising information about the collection of information about the environment.  Here we describe the implementation of a specialisation of O&M for environmental data, the Metadata Objects for Linking Environmental Sciences (MOLES3).MOLES3 provides support for organising information about data, and for user navigation around data holdings. The implementation described here, “CEDA-MOLES”, also supports data management functions for the Centre for Environmental Data Archival, CEDA. The previous iteration of MOLES (MOLES2) saw active use over five years, being replaced by CEDA-MOLES in late 2014. During that period important lessons were learnt both about the information needed, as well as how to design and maintain the necessary information systems. In this paper we review the problems encountered in MOLES2; how and why CEDA-MOLES was developed and engineered; the migration of information holdings from MOLES2 to CEDA-MOLES; and, finally, provide an early assessment of MOLES3 (as implemented in CEDA-MOLES) and its limitations.Key drivers for the MOLES3 development included the necessity for improved data provenance, for further structured information to support ISO19115 discovery metadata  export (for EU INSPIRE compliance), and to provide appropriate fixed landing pages for Digital Object Identifiers (DOIs) in the presence of evolving datasets. Key lessons learned included the importance of minimising information structure in free text fields, and the necessity to support as much agility in the information infrastructure as possible without compromising on maintainability both by those using the systems internally and externally (e.g. citing in to the information infrastructure), and those responsible for the systems themselves. The migration itself needed to ensure continuity of service and traceability of archived assets.

scholarly journals Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach

2020 ◽  
Vol 35 (12) ◽  
Author(s):  
Kye Hwa Lee ◽  
Hyo Jung Kim ◽  
Yi-Jun Kim ◽  
Ju Han Kim ◽  
Eun Young Song
Keyword(s):  
Free Text ◽  
Rule Based ◽  
Genotype Information ◽  
Rule Based Approach

scholarly journals Towards Adapting Cars to their Drivers

AI Magazine ◽  
2012 ◽  
Vol 33 (4) ◽  
pp. 46 ◽  
Author(s):  
Avi Rosenfeld ◽  
Zevi Bareket ◽  
Claudia V. Goldman ◽  
Sarit Kraus ◽  
David J. LeBlanc ◽  
...  
Keyword(s):  
Machine Learning Algorithms ◽  
Automated System ◽  
Expert Advice ◽  
Cruise Control ◽  
Learning Procedure ◽  
Combine Machine ◽  
Assistive Systems ◽  
Improved Learning ◽  
Current Systems ◽  
Interactive Activity

Traditionally, vehicles have been considered as machines that are controlled by humans for the purpose of transportation. A more modern view is to envision drivers and passengers as actively interacting with a complex automated system. Such interactive activity leads us to consider intelligent and advanced ways of interaction leading to cars that can adapt to their drivers.In this paper, we focus on the Adaptive Cruise Control (ACC) technology that allows a vehicle to automatically adjust its speed to maintain a preset distance from the vehicle in front of it based on the driver’s preferences. Although individual drivers have different driving styles and preferences, current systems do not distinguish among users. We introduce a method to combine machine learning algorithms with demographic information and expert advice into existing automated assistive systems. This method can reduce the interactions between drivers and automated systems by adjusting parameters relevant to the operation of these systems based on their specific drivers and context of drive. We also learn when users tend to engage and disengage the automated system. This method sheds light on the kinds of dynamics that users develop while interacting with automation and can teach us how to improve these systems for the benefit of their users. While generic packages such as Weka were successful in learning drivers’ behavior, we found that improved learning models could be developed by adding information on drivers’ demographics and a previously developed model about different driver types. We present the general methodology of our learning procedure and suggest applications of our approach to other domains as well.

Relational paraphrase acquisition from Wikipedia: The WRPA method and corpus

2013 ◽  
Vol 21 (3) ◽  
pp. 355-389 ◽  
Author(s):  
M. VILA ◽  
H. RODRÍGUEZ ◽  
M. A. MARTÍ
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
High Precision ◽  
Language Processing ◽  
The Body ◽  
Free Text ◽  
String Similarity ◽  
Distant Learning ◽  
Structured Information ◽  
Anchor Points

AbstractParaphrase corpora are an essential but scarce resource in Natural Language Processing. In this paper, we present the Wikipedia-based Relational Paraphrase Acquisition (WRPA) method, which extracts relational paraphrases from Wikipedia, and the derived WRPA paraphrase corpus. The WRPA corpus currently covers person-related and authorship relations in English and Spanish, respectively, suggesting that, given adequate Wikipedia coverage, our method is independent of the language and the relation addressed. WRPA extracts entity pairs from structured information in Wikipedia applying distant learning and, based on the distributional hypothesis, uses them as anchor points for candidate paraphrase extraction from the free text in the body of Wikipedia articles. Focussing on relational paraphrasing and taking advantage of Wikipedia-structured information allows for an automatic and consistent evaluation of the results. The WRPA corpus characteristics distinguish it from other types of corpora that rely on string similarity or transformation operations. WRPA relies on distributional similarity and is the result of the free use of language outside any reformulation framework. Validation results show a high precision for the corpus.

scholarly journals Efficacy of Once Daily versus Divided Daily Administration of Low Daily Dosage (15 mg/Day) of Methimazole in the Induction of Euthyroidism in Graves’ Hyperthyroidism: A Randomized Controlled Study

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Sutin Sriussadaporn ◽  
Wanwaroon Pumchumpol ◽  
Raweewan Lertwattanarak ◽  
Tada Kunavisarut
Keyword(s):  
Controlled Study ◽  
Once Daily ◽  
Randomized Controlled ◽  
Daily Dose ◽  
Cumulative Rate ◽  
Baseline Characteristics ◽  
Serum Thyroid Hormone ◽  
Thyroid Hormone Levels ◽  
Daily Dose Regimen ◽  
Clinical Trials Registry

Background. Previous studies used unequal or high daily dosages of methimazole (MMI) to compare the efficacy of once daily dose regimen (OD-MMI) with that of divided daily doses regimen (DD-MMI) in inducing euthyroidism. Objectives. To compare the efficacy of OD-MMI to that of DD-MMI using low daily dosage of MMI in inducing euthyroidism. Methods. Fifty patients with clinically nonsevere Graves’ hyperthyroidism were randomized to be treated with 15 mg/day OD-MMI or 15 mg/day DD-MMI. Results. 21 cases (84%) in OD-MMI and 23 cases (92%) in DD-MMI were eligible for analyses. During the treatment, there was no difference in baseline characteristics, serum FT3 and FT4 reductions, and cumulative rate of achieving euthyroidism (4.8% versus 4.3%, 28.6% versus 34.8%, 71.4% versus 82.6%, and 85.7% versus 87.0% at 2, 4, 8, and 12 weeks, resp.) between both regimens. Hypothyroidism developed in DD-MMI significantly more than in OD-MMI (17.4% versus 0%, p<0.05). Conclusions. Treatment with MMI at a low daily dosage of 15 mg/day OD-MMI is as effective as DD-MMI in the reduction of serum thyroid hormone levels and induction of euthyroidism. The OD-MMI regimen is preferable to the DD-MMI regimen in the treatment of clinically nonsevere Graves’ hyperthyroidism. This trial is registered with Thai Clinical Trials Registry: TCTR20170529001.

scholarly journals A Brief Intervention to Increase Uptake and Adherence of an Internet-Based Program for Depression and Anxiety (Enhancing Engagement With Psychosocial Interventions): Randomized Controlled Trial (Preprint)

2020 ◽  
Author(s):  
Philip J Batterham ◽  
Alison L Calear ◽  
Matthew Sunderland ◽  
Frances Kay-Lambkin ◽  
Louise M Farrer ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Behavioral Therapy ◽  
Controlled Trial ◽  
Psychosocial Interventions ◽  
P Uptake ◽  
Depression And Anxiety ◽  
Randomized Controlled ◽  
Significant Difference ◽  
The Difference ◽  
Clinical Trials Registry

BACKGROUND Psychosocial, self-guided, internet-based programs are effective in treating depression and anxiety. However, the community uptake of these programs is poor. Recent approaches to increasing engagement (defined as both uptake and adherence) in internet-based programs include brief engagement facilitation interventions (EFIs). However, these programs require evaluation to assess their efficacy. OBJECTIVE The aims of this hybrid implementation effectiveness trial are to examine the effects of a brief internet-based EFI presented before an internet-based cognitive behavioral therapy self-help program (<i>myCompass 2</i>) in improving engagement (uptake and adherence) with that program (primary aim), assess the relative efficacy of the <i>myCompass 2</i> program, and determine whether greater engagement was associated with improved efficacy (greater reduction in depression or anxiety symptoms) relative to the control (secondary aim). METHODS A 3-arm randomized controlled trial (N=849; recruited via social media) assessed the independent efficacy of the EFI and <i>myCompass 2</i>. The <i>myCompass 2</i> program was delivered with or without the EFI; both conditions were compared with an attention control condition. The EFI comprised brief (5 minutes), tailored audio-visual content on a series of click-through linear webpages. RESULTS Uptake was high in all groups; 82.8% (703/849) of participants clicked through the intervention following the pretest survey. However, the difference in uptake between the EFI + <i>myCompass 2</i> condition (234/280, 83.6%) and the <i>myCompass 2</i> alone condition (222/285, 77.9%) was not significant (n=565; <i>χ</i><sup>2</sup><sub>1</sub>=29.2; <i>P=</i>.09). In addition, there was no significant difference in the proportion of participants who started any number of modules (1-14 modules) versus those who started none between the EFI + <i>myCompass 2</i> (214/565, 37.9%) and the <i>myCompass 2</i> alone (210/565, 37.2%) conditions (n=565; <i>χ</i><sup>2</sup><sub>1</sub><0.1; <i>P=</i>.87). Finally, there was no significant difference between the EFI + <i>myCompass 2</i> and the <i>myCompass 2</i> alone conditions in the number of modules started (<i>U</i>=39366.50; <i>z</i>=−0.32; <i>P=</i>.75) or completed (<i>U</i>=39494.0; <i>z</i>=−0.29; <i>P=</i>.77). The <i>myCompass 2</i> program was not found to be efficacious over time for symptoms of depression (<i>F</i><sub>4,349.97</sub>=1.16; <i>P=</i>.33) or anxiety (<i>F</i><sub>4,445.99</sub>=0.12; <i>P=</i>.98). However, planned contrasts suggested that <i>myCompass 2</i> may have been effective for participants with elevated generalized anxiety disorder symptoms (<i>F</i><sub>4,332.80</sub>=3.50; <i>P=</i>.01). CONCLUSIONS This brief internet-based EFI did not increase the uptake of or adherence to an existing internet-based program for depression and anxiety. Individuals’ motivation to initiate and complete internet-based self-guided interventions is complex and remains a significant challenge for self-guided interventions. CLINICALTRIAL Australian New Zealand Clinical Trials Registry ACTRN12618001565235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375839

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