|Title||From episodes of care to diagnosis codes: automatic text categorization for medico-economic encoding.|
|Publication Type||Journal Article|
|Year of Publication||2008|
|Authors||Ruch, P, Gobeilla, J, Tbahritia, I, Geissbühlera, A|
|Journal||AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium|
|Keywords||Algorithms, Artificial Intelligence, Decision Support Systems, Clinical, Diagnosis, Computer-Assisted, Information Storage and Retrieval, International Classification of Diseases, Medical History Taking, Medical Records Systems, Computerized, Natural Language Processing, Pattern Recognition, Automated, Subject Headings, Switzerland|
We report on the design and evaluation of an original system to help assignment ICD (International Classification of Disease) codes to clinical narratives. The task is defined as a multi-class multi-document classification task. We combine a set of machine learning and data-poor methods to generate a single automatic text categorizer, which returns a ranked list of ICD codes. The combined ranking system currently obtains a precision of 75% at high ranks and a recall of about 63% for the top twenty returned codes for a theoretical upper bound of about 79% (inter-coder agreement). The performance of the data-poor classifier is weak, whereas the use of tempo-rally-typed contents such as anamnesis and prescription free text sections results in a statistically significant improvement.
|Alternate Journal||AMIA Annu Symp Proc|