According to the 'Istituto Superiore di Sanita (ISS), hospital infections are the most frequent and serious complication of health care. This constitutes a real health emergency which requires incisive and joint action at all levels of the local and national health organization. Most of the valuable information related to the presence of a specific microorganism in the blood are written into the notes field of the laboratory exams results. The main objective of this work is to build a Natural Language Processing (NLP) pipeline for the automatic extraction of the names of microorganisms present in the clinical texts. A sample of 499 microbiological notes have been analysed with the developed system and all the microorganisms names have been extracted correctly, according to the labels given by the expert.
CITATION STYLE
Mora, S., Attene, J., Gazzarata, R., Parruti, G., & Giacomini, M. (2021). A NLP pipeline for the automatic extraction of microorganisms names from microbiological notes. In Studies in Health Technology and Informatics (Vol. 285, pp. 153–158). IOS Press BV. https://doi.org/10.3233/SHTI210589
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