Evidence map›Paper›PMID 35978441›Full record

ArticleSystematic reviews2022

Reducing systematic review burden using Deduklick: a novel, automated, reliable, and explainable deduplication algorithm to foster medical research.

Nikolay Borissov, Quentin Haas, Beatrice Minder, Doris Kopp-Heim, Marc von Gernler, Heidrun Janka, Douglas Teodoro, Poorya Amini

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Systematic reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 25 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 25 pooled it
16.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed, 25 syntheses or guidelines pooled it, 97 citations in OpenAlex.

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  3. Nutrition and growth of primary ciliary dyskinesia patients: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026
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  13. Survival and Complications of Partial Coverage Restorations on Posterior Teeth-A Systematic Review and Meta-Analysis.Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.] · 2025
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  14. Survival and Complication Rates of Feldspathic, Leucite-Reinforced, Lithium Disilicate and Zirconia Ceramic Laminate Veneers: A Systematic Review and Meta-Analysis.Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.] · 2025
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4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Nikolay BorissovRisklick AG, Spin-Off, University of Bern, Bern, Switzerland.
Quentin HaasRisklick AG, Spin-Off, University of Bern, Bern, Switzerland.
Beatrice MinderPublic Health & Primary Care Library, University Library of Bern, University of Bern, Bern, Switzerland.
Doris Kopp-HeimPublic Health & Primary Care Library, University Library of Bern, University of Bern, Bern, Switzerland.
Marc von GernlerMedical Library, University Library of Bern, University of Bern, Bern, Switzerland.
Heidrun JankaMedical Library, University Library of Bern, University of Bern, Bern, Switzerland.
Douglas TeodoroUniversity of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland.
Poorya AminiRisklick AG, Spin-Off, University of Bern, Bern, Switzerland, . poorya.amini@risklick.ch.
University of Bern · CHUniversity of Geneva · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentifying and removing reference duplicates when conducting systematic reviews (SRs) remain a major, time-consuming issue for authors who manually check for duplicates using built-in features in citation managers. To address issues related to manual deduplication, we developed an automated, efficient, and rapid artificial intelligence-based algorithm named Deduklick. Deduklick combines natural language processing algorithms with a set of rules created by expert information specialists.

methodsDeduklick's deduplication uses a multistep algorithm of data normalization, calculates a similarity score, and identifies unique and duplicate references based on metadata fields, such as title, authors, journal, DOI, year, issue, volume, and page number range. We measured and compared Deduklick's capacity to accurately detect duplicates with the information specialists' standard, manual duplicate removal process using EndNote on eight existing heterogeneous datasets. Using a sensitivity analysis, we manually cross-compared the efficiency and noise of both methods. DISCUSSION: Deduklick achieved average recall of 99.51%, average precision of 100.00%, and average F1 score of 99.75%. In contrast, the manual deduplication process achieved average recall of 88.65%, average precision of 99.95%, and average F1 score of 91.98%. Deduklick achieved equal to higher expert-level performance on duplicate removal. It also preserved high metadata quality and drastically reduced time spent on analysis. Deduklick represents an efficient, transparent, ergonomic, and time-saving solution for identifying and removing duplicates in SRs searches. Deduklick could therefore simplify SRs production and represent important advantages for scientists, including saving time, increasing accuracy, reducing costs, and contributing to quality SRs.

Indexed as

AlgorithmsArtificial IntelligenceSystematic Reviews as TopicBiomedical ResearchHumansNatural Language ProcessingArtificial intelligenceBibliographic databasesDeduplicationDuplicate referencesRisklickSystematic reviewSystematic review software

Identifiers

PMID35978441
PMCPMC9382798
OpenAlexW4292262803

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.