Skip to content
ASReview
AI-aided Systematic Reviewing
ASReview
  • Install
  • Product
    • Screen
    • AI
    • Simulate
    • Crowdscreen
  • Solutions
    • For screeners
    • For information specialists
    • For data scientists
    • For developers
    • For institutions
    • For students
  • Resources
    • Documentation
    • Donate
    • Events
    • Reads
Search:
Github page opens in new window
  • Install
  • Product
    • Screen
    • AI
    • Simulate
    • Crowdscreen
  • Solutions
    • For screeners
    • For information specialists
    • For data scientists
    • For developers
    • For institutions
    • For students
  • Resources
    • Documentation
    • Donate
    • Events
    • Reads

rutger

Introducing the Noisy Label Filter (NLF) procedure in systematic reviews

Long readsBy rutgerSeptember 25, 2023

The ASReview team developed a procedure to overcome replication issues in creating a dataset for simulation studies to evaluate the performance of active learning models! In this blog post, we explain this procedure, called the “Noisy Label Filter (NLF) Procedure”. Background: Labelled Data needed for a Simulation Study In an ASReview simulation study, you can…

ZoomDetails

The Noisy Label Filter procedure: a case study to address replication issues in systematic reviews

Data, Scientific Papers, Simulation Studies, Special Use-CasesBy rutgerAugust 29, 2023

In this study, we addressed the issue of the lack of replicability of systematic reviews datasets. We used a case study format and developed a procedure to optimize and finalize the by rule imperfect reconstructed dataset.

About

Team
Community
Code of Conduct
Methodology & Statistics

Research

Disc AI-Lab
Version 2.0
Scientifically proven
Write grants with us

Resources

Discussion
Newsletter
Documentation
Zotero database

Socials

GitHub
LinkedIn
YouTube

Go to Top