PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 3, 2026Computer Methods and Programs in Biomedicine0 citationsOpen Access

A novel indirect method for deriving reference intervals through iterative data cleaning guided by self-organizing maps of multi-test patterns (SOM-clean)

View Full Paper
KIKiyoshi IchiharaTYTeppei YamashitaABAnwar Borai

Key Points

  • This method enhances the accuracy of reference intervals derived from laboratory data, improving clinical decision-making.
  • Using novel self-organizing maps, reference intervals were estimated with greater precision than traditional methods.
  • SOM-clean utilizes a multivariate approach to data cleaning, ensuring robust results across various tests.
  • The implications support better understanding and implementation of reference intervals in clinical settings.

Abstract

SOM-clean represents a practical and robust parametric tool for estimating RIs indirectly from routine laboratory data employing a novel multivariate-based data cleaning scheme.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ichihara et al. (2026) studied this question.

synapsesocial.com/papers/69a766e3badf0bb9e87decbdhttps://doi.org/10.1016/j.cmpb.2026.109279
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Derivation of sex and age-specific reference intervals for clinical chemistry analytes in healthy Ghanaian adults2022 · 20 citations
  2. 2A global multicenter study on reference values: 1. Assessment of methods for derivation and comparison of reference intervals2016 · 104 citations
  3. 3Reference intervals for 33 biochemical analytes in healthy Indian population: C-RIDL IFCC initiative2018 · 49 citations
  4. 4Critical appraisal of two Box-Cox formulae for their utility in determining reference intervals by realistic simulation and extensive real-world data analyses2023 · 8 citations
  5. 5A Novel Bioinformatics Strategy to Analyze Microbial Big Sequence Data for Efficient Knowledge Discovery: Batch-Learning Self-Organizing Map (BLSOM)2013 · 16 citations