CLINIQA: A Machine Intelligence Based Clinical Question Answering System
| Autor: | Zahid, M A H, Mittal, Ankush, Joshi, R. C., Atluri, G. |
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| Rok vydání: | 2018 |
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| Druh dokumentu: | Working Paper |
| Popis: | The recent developments in the field of biomedicine have made large volumes of biomedical literature available to the medical practitioners. Due to the large size and lack of efficient searching strategies, medical practitioners struggle to obtain necessary information available in the biomedical literature. Moreover, the most sophisticated search engines of age are not intelligent enough to interpret the clinicians' questions. These facts reflect the urgent need of an information retrieval system that accepts the queries from medical practitioners' in natural language and returns the answers quickly and efficiently. In this paper, we present an implementation of a machine intelligence based CLINIcal Question Answering system (CLINIQA) to answer medical practitioner's questions. The system was rigorously evaluated on different text mining algorithms and the best components for the system were selected. The system makes use of Unified Medical Language System for semantic analysis of both questions and medical documents. In addition, the system employs supervised machine learning algorithms for classification of the documents, identifying the focus of the question and answer selection. Effective domain-specific heuristics are designed for answer ranking. The performance evaluation on hundred clinical questions shows the effectiveness of our approach. Comment: This manuscript was submitted to IEEE Transactions on Information Technology in Biomedicine in 2007 and was in second revision when it was withdrawn. As I moved to industry and could not get enough time to revise it. I am uploading it here for anyone interested in conventional ML based approach to NLP |
| Databáze: | arXiv |
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