Machine learning can identify newly diagnosed patients with CLL at high risk of infection

Machine learning can identify newly diagnosed patients with CLL at high risk of infection

Chronic lymphocytic leukemia is an indolent disease, and many patients succumb to infection rather than the direct effects of the disease. Here, the authors use medical records and machine learning to predict the patients that may be at risk of infection, which may enable a change in the course of t...

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Autores principales: Rudi Agius, Christian Brieghel, Michael A. Andersen, Alexander T. Pearson, Bruno Ledergerber, Alessandro Cozzi-Lepri, Yoram Louzoun, Christen L. Andersen, Jacob Bergstedt, Jakob H. von Stemann, Mette Jørgensen, Man-Hung Eric Tang, Magnus Fontes, Jasmin Bahlo, Carmen D. Herling, Michael Hallek, Jens Lundgren, Cameron Ross MacPherson, Jan Larsen, Carsten U. Niemann
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Science
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Acceso en línea:https://doaj.org/article/d34aa0eace4042dc8ea0d505bfcb57d5
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Sumario:Chronic lymphocytic leukemia is an indolent disease, and many patients succumb to infection rather than the direct effects of the disease. Here, the authors use medical records and machine learning to predict the patients that may be at risk of infection, which may enable a change in the course of their treatment.

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