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15 March 2019 A knowledge-based question answering system to provide cognitive assistance to radiologists
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With the advent of computers and natural language processing, it is not surprising to see that humans are trying to use computers to answer questions. By the 1960s, there were systems implemented on the two major models of question answering, IR-based and knowledge-based, to answer questions about sport statistics and scientific facts. This paper reports on the development of a knowledge-based question answering system that is aimed at providing cognitive assistance to radiologists. Our system represents the question as a semantic query to a medical knowledge base. Evidence obtained from textual and imaging data associated with the question is then combined to arrive at an answer. This question answering system has 3 stages: i) question text and answer choices processing, ii) image processing, and iii) reasoning. Currently, the system can answer differential diagnosis and patient management questions, however, we can tackle a wider variety of question types by improving our medical knowledge coverage in the future.
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Anup Pillai, Amin Katouzian, Karina Kanjaria, Chaitanya Shivade, Ashutosh Jadhav, Marina Bendersky, Vandana Mukherjee, and Tanveer Syeda-Mahmood "A knowledge-based question answering system to provide cognitive assistance to radiologists", Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 1095418 (15 March 2019);

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