ArticleContact in context2023
Nonparametric Subcluster Detection in Large Hyperspaces.
Article in Contact in context, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
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- Measuring Aztreonam Variations by Process Analytical Technology.Contact in context · 2026Article
- Spectrometric Assessment of Intralot and Interlot Variability in Mycophenolate Mofetil for Injection Using Near-Infrared Spectrometry and Nonparametric Subcluster Detection.Contact in context · 2026Article
- Near-Infrared Spectrometry as a Tool for Screening Meropenem for Quality.Contact in context · 2025Article
- Rapid Quality Assessment of Ceftriaxone Using Near-Infrared Spectroscopy.Contact in context · 2025Article
- NIR Spectrometry Reveals Lack of Content Uniformity in Methylprednisolone Sodium Succinate.Contact in context · 2025Article
- Fourier Transform Near-Infrared Spectrometry Reveals Significant Inter-Lot Variability in Thyrotropin Alfa (ThyrogenContact in context · 2025Article
- Lack of Content Uniformity in Azacitidine Vials.Contact in context · 2024Article
- Application of Near-Infrared Spectroscopy for Screening of Chlorothiazide Sodium Vials.Contact in context · 2024Article
- Potential Process Control Issues with Vasopressin.Contact in context · 2024Article
- Potential Process Control Issues With Abatacept.Contact in context · 2024Article
- Assessment of Vecuronium Quality Using Near-Infrared Spectrometry.Contact in context · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
This assessment of subcluster detection in analytical chemistry offers a nonparametric approach to address the challenges of identifying specific substances (molecules or mixtures) in large hyperspaces. The paper introduces the concept of subcluster detection, which involves identifying specific substances within a larger cluster of similar samples. The BEST (Bootstrap Error-adjusted Single-sample Technique) metric is introduced as a more accurate and precise method for discriminating between similar samples compared to the MD (Mahalanobis distance) metric. The paper also discusses the challenges of subcluster detection in large hyperspaces, such as the curse of dimensionality and the need for nonparametric methods. The proposed nonparametric approach involves using a kernel density estimator to determine the probability density function of the data and then using a quantile-quantile algorithm to identify subclusters. The paper provides examples of how this approach can be used to analyze small changes in the near-infrared spectra of drug samples and identifies the benefits of this approach, such as improved accuracy and precision.
Identifiers
39291094PMC11407754What OpenQuestion holds
Registered trials
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.