SemBioNLQA: A semantic biomedical question answering system for retrieving exact and ideal answers to natural language questions

Publication date: Available online 28 November 2019Source: Artificial Intelligence in MedicineAuthor(s): Mourad Sarrouti, Said Ouatik El AlaouiAbstractBackground and objectiveQuestion answering (QA), the identification of short accurate answers to users questions written in natural language expressions, is a longstanding issue widely studied over the last decades in the open-domain. However, it still remains a real challenge in the biomedical domain as the most of the existing systems support a limited amount of question and answer types as well as still require further efforts in order to improve their performance in terms of precision for the supported questions. Here, we present a semantic biomedical QA system named SemBioNLQA which has the ability to handle the kinds of yes/no, factoid, list, and summary natural language questions.MethodsThis paper describes the system architecture and an evaluation of the developed end-to-end biomedical QA system named SemBioNLQA, which consists of question classification, document retrieval, passage retrieval and answer extraction modules. It takes natural language questions as input, and outputs both short precise answers and summaries as results. The SemBioNLQA system, dealing with four types of questions, is based on (1) handcrafted lexico-syntactic patterns and a machine learning algorithm for question classification, (2) PubMed search engine and UMLS similarity for document retrieval, (3) the BM25 model, stemmed words and UMLS conc...
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research