Clinical narratives are a valuable source of information for both patient care and biomedical
research. Given the unstructured nature of medical reports, specific automatic techniques …

Objective In this work, we propose an ontology-driven approach to identify events and their
attributes from episodes of care included in medical reports written in Italian. For this …

Medical reports include many occurrences of relevant events in the form of free-text. To
make data easily accessible and improve medical decisions, clinical information extraction …

Data extraction from narrative medical texts is a significant task to enable secondary use of
medical data. Supervised learning algorithms show good results in natural language …

Automatic classification of diagnoses has been a long term challenge for Computer Science
and related disciplines. Textual clinical reports can be used as a great source of data for …

Objective Identification of clinical events (eg, problems, tests, treatments) and associated
temporal expressions (eg, dates and times) are key tasks in extracting and managing data …

Textual data are useful to access expert information. Since the texts are representative of
distinct language uses, it is necessary to build specific corpora in order to be able to design …

Extracting information from unstructured clinical narratives is valuable for many clinical
applications. Although natural Language Processing (NLP) methods have been profoundly …

An Approach for Automatic Classification of Radiology Reports in Spanish Page 1 An Approach
for Automatic Classification of Radiology Reports in Spanish Viviana Cotik a , Darío Filippo b …

Clinical reports often include descriptions of events in the patient's medical history, as well
as explicit or implicit temporal information about these events. We are working towards …