In a context of digitalization and modernization of healthcare, automatic analysis of clinical data plays a leading role in improving the quality of care. Since much of the information lies in an unstructured form within clinical notes, it is necessary to make use of modern Natural Language Processing techniques to extract and build structured knowledge from the data. However, clinical texts pose unique challenges due to the extensive usage of i) acronyms, ii) non-standard medical jargons and iii) typos over technical terms. In this paper, we present a prototype spell-checker specifically designed for medical texts written in Italian.
A Support for Understanding Medical Notes: Correcting Spelling Errors in Italian Clinical Records / Ferrod, Roger; Brunetti, Enrico; Di Caro, Luigi; Di Francescomarino, Chiara; Dragoni, Mauro; Ghidini, Chiara; Marinello, Renata; Sulis, Emilio. - 3060:(2021), pp. 19-28. (Intervento presentato al convegno 20th International Conference ofthe Italian Association for Artificial Intelligence (AIxIA2021) nel November 29th, 2021).
A Support for Understanding Medical Notes: Correcting Spelling Errors in Italian Clinical Records
Chiara Di Francescomarino;Mauro Dragoni;
2021-01-01
Abstract
In a context of digitalization and modernization of healthcare, automatic analysis of clinical data plays a leading role in improving the quality of care. Since much of the information lies in an unstructured form within clinical notes, it is necessary to make use of modern Natural Language Processing techniques to extract and build structured knowledge from the data. However, clinical texts pose unique challenges due to the extensive usage of i) acronyms, ii) non-standard medical jargons and iii) typos over technical terms. In this paper, we present a prototype spell-checker specifically designed for medical texts written in Italian.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
