ReviewWiley interdisciplinary reviews. Computational statistics
Stability estimation for unsupervised clustering: A review.
Review in Wiley interdisciplinary reviews. Computational statistics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and meta-analysis of disease clusters in multimorbidity.Nature communications · 2025Pooled it
- Accurate Identification of Key Groups of Microeukaryotes Using Multimodal Deep Learning: An Integrated Classification Model Combining Morphological and Molecular Data.Molecular ecology resources · 2026Article
- Movement-Based Low Back Pain Subgroups Using Motion Tape Strain Data with Biomechanical and Causal Feature Engineering.Sensors (Basel, Switzerland) · 2026Article
- Identification of distinct clinical phenotypes and their neurobiological signatures in stress-exposed individuals: A multimodal machine learning approach.European psychiatry : the journal of the Association of European Psychiatrists · 2026Article
- Geometric morphometrics based diagnostic model for Skeletal Class III patients.Communications medicine · 2026Article
- Analytic challenges in defining structural phenotypes in OA clinical trials: a perspective.Osteoarthritis imaging · 2025Article
- Identification and validation of postpartum depression subtypes: a population-based cohort study.EClinicalMedicine · 2025Article
- Key research priorities in methodological approaches for measuring the exposome and studying its role in the development of dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Unsupervised clustering for sepsis identification in large-scale patient data: a model development and validation study.Intensive care medicine experimental · 2025Article
- Human AI collaboration for unsupervised categorization of live surgical feedback.NPJ digital medicine · 2024Article
- Robustness assessment of regressions using cluster analysis typologies: a bootstrap procedure with application in state sequence analysis.BMC medical research methodology · 2024Article
- Clustering Methods in Rheumatic and Musculoskeletal Disease Research: An Educational Guide to Best Research Practices.The Journal of rheumatology · 2024Review
- Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma.Communications biology · 2024Article
- The cluster D-trace loss for differential network analysis.Journal of applied statistics · 2024Article
- Systematic review and meta-analysis of disease clustering in multimorbidity: a study protocol.BMJ open · 2023Article
- Comparative Analysis of the Clustering Quality in Self-Organizing Maps for Human Posture Classification.Sensors (Basel, Switzerland) · 2023Article
- Multi-view clustering by CPS-merge analysis with application to multimodal single-cell data.PLoS computational biology · 2023Article
- Clustering Deviation Index (CDI): a robust and accurate internal measure for evaluating scRNA-seq data clustering.Genome biology · 2022Article
- Stability estimation for unsupervised clustering: A review.Wiley interdisciplinary reviews. Computational statisticsReview
- A methodological study of clustering evaluation in medical data: Exploring internal and stability-based criteria.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Cluster analysis remains one of the most challenging yet fundamental tasks in unsupervised learning. This is due in part to the fact that there are no labels or gold standards by which performance can be measured. Moreover, the wide range of clustering methods available is governed by different objective functions, different parameters, and dissimilarity measures. The purpose of clustering is versatile, often playing critical roles in the early stages of exploratory data analysis and as an endpoint for knowledge and discovery. Thus, understanding the quality of a clustering is of critical importance. The concept of
Indexed as
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What 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.