Clinical timelines development from textual medical reports in Italian

Patients diagnosed with chronic conditions are visited multiple times over the years. The medical reports produced during these visits often include valuable knowledge in the form of free text. To help physician access and review this knowledge, natural language processing and aggregation techniques are needed. In this work, we propose a system that extracts and summarizes information from medical reports written in Italian. For each patient, the system builds and visualizes a timeline of the extracted events. The proposed approach has the potential to enhance the process of reviewing patient clinical histories, reducing the time needed to access large amounts of data. In the future, an extension of the visualized timeline and an extrinsic evaluation will be performed.

[1]  Francesco Pinciroli,et al.  Use of "off-the-shelf" information extraction algorithms in clinical informatics: A feasibility study of MetaMap annotation of Italian medical notes , 2016, J. Biomed. Informatics.

[2]  Hongfang Liu,et al.  CliniViewer: A Tool for Viewing Electronic Medical Records Based on Natural Language Processing and XML , 2004, MedInfo.

[3]  Wendy W. Chapman,et al.  ConText: An algorithm for determining negation, experiencer, and temporal status from clinical reports , 2009, J. Biomed. Informatics.

[4]  Noémie Elhadad,et al.  Automated methods for the summarization of electronic health records , 2015, J. Am. Medical Informatics Assoc..

[5]  David K. Vawdrey,et al.  HARVEST, a longitudinal patient record summarizer , 2014, J. Am. Medical Informatics Assoc..

[6]  Carol Friedman,et al.  A broad-coverage natural language processing system , 2000, AMIA.

[7]  E. Tufte,et al.  Graphical summary of patient status , 1994, The Lancet.

[8]  S Velupillai,et al.  Recent Advances in Clinical Natural Language Processing in Support of Semantic Analysis , 2015, Yearbook of Medical Informatics.

[9]  Giuseppe Attardi,et al.  Annotation and Extraction of Relations from Italian Medical Records , 2015, IIR.

[10]  Adam Wright,et al.  Summarization of clinical information: A conceptual model , 2011, J. Biomed. Informatics.

[11]  Clement J. McDonald,et al.  What can natural language processing do for clinical decision support? , 2009, J. Biomed. Informatics.

[12]  Hooshang Kangarloo,et al.  Problem-centric organization and visualization of patient imaging and clinical data. , 2009, Radiographics : a review publication of the Radiological Society of North America, Inc.

[13]  Chen Lin,et al.  Temporal Annotation in the Clinical Domain , 2014, TACL.

[14]  David A. Ferrucci,et al.  UIMA: an architectural approach to unstructured information processing in the corporate research environment , 2004, Natural Language Engineering.

[15]  Riccardo Bellazzi,et al.  Information Extraction from Italian medical reports: first steps towards clinical timelines development , 2016, AMIA.