GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil.
Methods Mol Biol. 2022;2511:375-394. doi: 10.1007/978-1-0716-2395-4_29.
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.
机器学习正被应用于多种疾病的诊断方法的开发,但预后技术仍在探索中。开发这种方法对于帮助医疗保健工作者确保为患者提供最合适的治疗至关重要。在本章中,我们展示了一个详细的方案,即应用机器学习对 COVID-19 感染血浆样本的 MALDI-TOF MS 光谱进行风险分类和生物标志物识别。