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Ruggero Guerrini

University of Lille

Lille, F-59000

France

  • University of Lille

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Scholarly Papers (1)

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Quality-Driven Divisive K-Means: A New Clustering Strategy for Maldi Imaging Data for a More Precise and Less Biased Characterization of Complex Biological Tissues

Number of pages: 11 Posted: 06 Jun 2025
Ruggero Guerrini, Nina Ogrinc, Emilien Colin, Riad Tebbakha, Christophe Attencourt, Ahmed Boudahi, Sylvie Testelin, Stéphanie Dakpé, Isabelle Fournier and Ludovic Duponchel
University of Lille, Université de Lille - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Université de Lille - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM and University of Lille
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Abstract:

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MALDI-MSI, Biological tissues, imaging, Chemometrics, machine learning