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Machine Learning Approaches to Analyze MALDI-TOF Mass Spectrometry Protein Profiles.
Lazari, Lucas C; Rosa-Fernandes, Livia; Palmisano, Giuseppe.
  • Lazari LC; GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil.
  • Rosa-Fernandes L; GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil.
  • Palmisano G; GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil. palmisano.gp@gmail.com.
Methods Mol Biol ; 2511: 375-394, 2022.
Article in English | MEDLINE | ID: covidwho-1941391
ABSTRACT
Machine learning is being employed for the development of diagnostic methods for several diseases, but prognostic techniques are still poorly explored. The development of such approaches is essential to assist healthcare workers to ensure the most appropriate treatment for patients. In this chapter, we demonstrate a detailed protocol for the application of machine learning to MALDI-TOF MS spectra of COVID-19-infected plasma samples for risk classification and biomarker identification.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-2395-4_29

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-2395-4_29