Er Khushbu GuptaRatchainant ThammasudjaritAmmarin ThakkinstianFaculty of Medicine, Ramathibodi Hospital, Mahidol University2020-01-272020-01-272019-07-01JCSSE 2019 - 16th International Joint Conference on Computer Science and Software Engineering: Knowledge Evolution Towards Singularity of Man-Machine Intelligence. (2019), 293-2972-s2.0-85074239572https://repository.li.mahidol.ac.th/handle/20.500.14594/50628© 2019 IEEE. Clinical researches and practitioners require data extracted from CT scan reports but most of them are in unstructured data format, which are not ready to analysis. Furthermore, a lag of annotated data makes data extraction more difficult to apply natural language processing techniques to convert unstructured data to be structured data. This study is therefore conducted to apply an automated engine employing topic modeling combined with lexicon and syntactic rule-based approach to extract clinical information from CT scan reports. This prototype shows promising results for constructing clinical datasets for further clinical researches.Mahidol UniversityComputer ScienceDecision SciencesConference PaperSCOPUS10.1109/JCSSE.2019.8864178