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|Title:||Text mining in radiology reports|
|Source:||Gong, T., Tan, C.L., Yun, L.T., Lee, C.K., Pang, B.C., Lim, C.C.T., Tian, Q., Tang, S., Zhang, Z. (2008). Text mining in radiology reports. Proceedings - IEEE International Conference on Data Mining, ICDM : 815-820. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDM.2008.150|
|Abstract:||Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologist's observations on the patient's medical conditions in the associated medical images. However, as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied. In this paper, we propose a text mining system to extract and use the information in radiology reports. The system consists of three main modules: a medical finding extractor, a report and image retriever, and a text-assisted image feature extractor. In evaluation, the overall precision and recall for medical finding extraction are 95.5% and 87.9% respectively, and for all modifiers of the medical findings 88.2% and 82.8% respectively. The overall result of report and image retrieval module and text-assisted image feature extraction module is satisfactory to radiologists. ©2008 IEEE.|
|Source Title:||Proceedings - IEEE International Conference on Data Mining, ICDM|
|Appears in Collections:||Staff Publications|
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