The growing number of medical literature and textual data in online repositories led to an exponential increase in the workload of researchers involved in citation screening for systematic reviews. This work aims to combine machine learning techniques and data preprocessing for class imbalance to identify the outperforming strategy to screen articles in PubMed for inclusion in systematic reviews.

Screening PubMed abstracts: is class imbalance always a challenge to machine learning?

Lanera, Corrado;Berchialla, Paola;Minto, Clara;Gregori, Dario;Baldi, Ileana
2019

Abstract

The growing number of medical literature and textual data in online repositories led to an exponential increase in the workload of researchers involved in citation screening for systematic reviews. This work aims to combine machine learning techniques and data preprocessing for class imbalance to identify the outperforming strategy to screen articles in PubMed for inclusion in systematic reviews.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3318080
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