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November, 2026
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Felipe Magalhaes Furtado: Artificial Intelligence Advances PNH Clone Detection Through Machine Learning
Nov 14, 2026, 23:33

Felipe Magalhaes Furtado: Artificial Intelligence Advances PNH Clone Detection Through Machine Learning

Felipe Magalhaes Furtado, Hematologist at Sabin Medicina Diagnóstica, shared a post on LinkedIn about a recent article he and his colleagues co-authored, published in Cytometry Part B: Clinical Cytometry, adding:

“I am pleased to share our recently published article in Cytometry Part B: Clinical Cytometry: ‘Artificial intelligence-based screening of paroxysmal nocturnal hemoglobinuria clones: Development and comparative evaluation of machine learning models.’

This study explores the application of machine learning to flow cytometry, focusing on the identification of paroxysmal nocturnal hemoglobinuria (PNH) clones.

I would like to express my gratitude to the faculty and staff of the MBA USP/Esalq MBA in Data Science and Analytics at USP/ESALQ, whose teaching and support were fundamental to the development of this project.

I am also grateful to Grupo Sabin for making this research possible.

My sincere thanks also go to Alan Carvalho Dias, André Pinto, Adâmara S. G. Felício, Camila S. Nobre, Fernanda Resende, my co-authors, whose expertise, contributions, and collaboration were essential to making this work possible.

It is a particular honor to see this research published in Cytometry Part B, a journal that has made significant contributions to the field of clinical cytometry.

I hope our findings contribute to further discussions and developments in the application of artificial intelligence to laboratory medicine.”

Title: Artificial intelligence-based screening of paroxysmal nocturnal hemoglobinuria clones: Development and comparative evaluation of machine learning models

Authors: Felipe Magalhães Furtado, Fernanda de Oliveira Resende, Camila Santos Nobre, Alan Carvalho Dias, André Luiz Pinto, Adamara Felício

Felipe Magalhaes Furtado: Artificial Intelligence Advances PNH Clone Detection Through Machine Learning

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