This paper is in the following e-collection/theme issue:

Reviews in Medical Informatics (104) Clinical Informatics (1248) Clinical Information and Decision Making (1798) Ontologies, Classifications, and Coding (307)

Published on in Vol 8, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16452, first published .
Challenges of Clustering Multimodal Clinical Data: Review of Applications in Asthma Subtyping

Challenges of Clustering Multimodal Clinical Data: Review of Applications in Asthma Subtyping

Challenges of Clustering Multimodal Clinical Data: Review of Applications in Asthma Subtyping

Authors of this article:

Elsie Horne1 Author Orcid Image ;   Holly Tibble1 Author Orcid Image ;   Aziz Sheikh1 Author Orcid Image ;   Athanasios Tsanas1 Author Orcid Image
Article Authors Cited by (33) Tweetations (10) Metrics

Journals

  1. Keenan T. The Hitchhiker’s Guide to Cluster Analysis: Multi Pertransibunt et Augebitur Scientia. Ophthalmology Retina 2020;4(12):1125 View
  2. Genitsaridi E, Hoare D, Kypraios T, Hall D. A Review and a Framework of Variables for Defining and Characterizing Tinnitus Subphenotypes. Brain Sciences 2020;10(12):938 View
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  5. Horne E, McLean S, Alsallakh M, Davies G, Price D, Sheikh A, Tsanas A. Defining clinical subtypes of adult asthma using electronic health records: Analysis of a large UK primary care database with external validation. International Journal of Medical Informatics 2023;170:104942 View
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  10. Patriarca R, Simone F, Di Gravio G. Supporting weather forecasting performance management at aerodromes through anomaly detection and hierarchical clustering. Expert Systems with Applications 2023;213:119210 View
  11. Tsang K, Pinnock H, Wilson A, Shah S. Application of Machine Learning Algorithms for Asthma Management with mHealth: A Clinical Review. Journal of Asthma and Allergy 2022;Volume 15:855 View
  12. Tsanas A, Arora S. Data-Driven Subtyping of Parkinson’s Using Acoustic Analysis of Sustained Vowels and Cluster Analysis: Findings in the Parkinson’s Voice Initiative Study. SN Computer Science 2022;3(3) View
  13. Munns A, Wiffen L, Brown T, Fasulo A, Chauhan M, D'Cruz L, Kaklamanou D, Chauhan A. Capability, Opportunity, and Motivation Model for Behavior Change in People With Asthma: Protocol for a Cross-Sectional Study. JMIR Research Protocols 2023;12:e44710 View
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  15. Zahraei H, Schleich F, Gerday S, Guissard F, Paulus V, Henket M, Moermans C, Donneau A, Louis R. A clustering analysis of eosinophilic asthmatics: Two clusters with sharp differences in atopic status and disease severity. Clinical & Experimental Allergy 2023;53(6):672 View
  16. Radhoe T, Agelink van Rentergem J, Torenvliet C, Groenman A, van der Putten W, Geurts H. Finding Similarities in Differences Between Autistic Adults: Two Replicated Subgroups. Journal of Autism and Developmental Disorders 2024;54(9):3449 View
  17. Dhafari T, Pate A, Azadbakht N, Bailey R, Rafferty J, Jalali-najafabadi F, Martin G, Hassaine A, Akbari A, Lyons J, Watkins A, Lyons R, Peek N. A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods. Journal of Clinical Epidemiology 2024;165:111214 View
  18. Yang M, Matan-Lithwick S, Wang Y, De Jager P, Bennett D, Felsky D. Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing. Brain Communications 2023;5(2) View
  19. Zahraei H, Schleich F, Louis G, Gerday S, Sabbe M, Bougard N, Guissard F, Paulus V, Henket M, Petre B, Donneau A, Louis R. Evidence for 2 clusters among patients with noneosinophilic asthma. Annals of Allergy, Asthma & Immunology 2024;133(1):57 View
  20. Palomino-Echeverria S, Huergo E, Ortega-Legarreta A, Uson Raposo E, Aguilar F, Peña-Ramirez C, López-Vicario C, Alessandria C, Laleman W, Queiroz Farias A, Moreau R, Fernandez J, Arroyo V, Caraceni P, Lagani V, Sánchez-Garrido C, Clària J, Tegner J, Trebicka J, Kiani N, Planell N, Rautou P, Gomez-Cabrero D. A robust clustering strategy for stratification unveils unique patient subgroups in acutely decompensated cirrhosis. Journal of Translational Medicine 2024;22(1) View
  21. Ngai S, Cheung C, Ng Y, Lee B, Dupéré V, Wang M, Chen C, Li Y, Zhou Q, Wong L, Zhang X. Pathways from school to work: A sequence analysis of non‐engaged youth. Journal of Adolescence 2024;96(7):1655 View
  22. Hassan B, Tayfor N, Hassan A, Ahmed A, Rashid T, Abdalla N. From A-to-Z review of clustering validation indices. Neurocomputing 2024;601:128198 View
  23. Kreienkamp J, Agostini M, Monden R, Epstude K, de Jonge P, Bringmann L. A Gentle Introduction and Application of Feature-Based Clustering with Psychological Time Series. Multivariate Behavioral Research 2025;60(2):362 View
  24. Liu P, Yuan H, Ning Y, Chakraborty B, Liu N, Peres M. A modified and weighted Gower distance-based clustering analysis for mixed type data: a simulation and empirical analyses. BMC Medical Research Methodology 2024;24(1) View
  25. Zhang Z, Yoshimura H, Acosta-Mena D, Teixeira C, Finan C, Lip G, Schmidt A, Providencia R. Clustering of electronic health records in atrial fibrillation patients and impact on prognosis and patient trajectories: a UK linked-dataset study. European Heart Journal - Digital Health 2025;6(4):797 View
  26. Lee I, Ganesan A, Kalesinskas L, Zheng H, Ahn H, Christenson S, Erzurum S, Zein J, Bleecker E, Meyers D, Castro M, Fahy J, Israel E, Jarjour N, Moore W, Wenzel S, Mauger D, Levy B, Woodruff P, Ortega V, Khatri P. Multicohort Analysis of Bronchial Epithelial Cell Expression in Healthy Subjects and Patients with Asthma Reveals Four Clinically Distinct Clusters. American Journal of Respiratory Cell and Molecular Biology 2025;73(1):73 View
  27. Al-Mamun M, Jeun K, Brothers T, Asare E, Shawwa K, Ahmed I, Kaewput W. Evaluating the kidney disease progression using a comprehensive patient profiling algorithm: A hybrid clustering approach. PLOS One 2025;20(7):e0310749 View
  28. Lisik D, Shah S, Basna R, Dinh T, Browne R, Andrews J, Wallace M, Ezugwu A, Marusic A, Tran D, Torres-Sospedra J, Dam H, Fournier-Viger P, Hennig C, Timmerman M, Warrens M, Ceulemans E, Nwaru B, Hernandez-Boussard T. Protocol for development of a checklist and guideline for transparent reporting of cluster analyses (TRoCA). BMJ Open 2025;15(8):e099609 View

Books/Policy Documents

  1. Nadif R, Savouré M. Asthma in the 21st Century. View

Conference Proceedings

  1. Bogatyrev M, Shestaka T. Proceedings of the International Conference "Mathematical Biology and Bioinformatics". Multimodal clustering in the data analysis of myocardial infarction complications View
  2. Kumar R, Nagalakshmi T. FIFTH INTERNATIONAL CONFERENCE ON APPLIED SCIENCES: ICAS2023. Design of intrusion detection system in the detection of grey hole attack in wireless ad hoc network using K-means cluster comparing with decision tree View
  3. Arystambekova A, Pinsky E. ITISE 2025. Enhancing Public Health Insights and Interpretation Through AI-Driven Time-Series Analysis: Hierarchical Clustering, Hamming Distance, and Binary Tree Visualization of Infectious Disease Trends View

Dissertations

  1. . Wearables in Healthcare: Popular Topics and Sentiments in Reddit and a Preliminary Quantitative Study on Health Professionals’ Wearable Adoption. View