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- W4386938228 abstract "With the increasing amount of electronic biomedical research available, it is becoming difficult for scientists and researchers to effectively access and process this information. In this study, a framework is proposed for biomedical information retrieval using state-of-the-art transformer-based natural language processing methods, focusing on discovering genetic relationships and mechanisms that contribute to diseases and other health conditions. Data processing, model evaluation and algorithm transparency through the use explainable artificial intelligence are proposed as the key components of the methodology. The framework is explained and demonstrated in the context of COVID-19 in a topical and systematic manner, and is designed so that it can be adapted for use in other biomedical settings." @default.
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- W4386938228 date "2023-01-01" @default.
- W4386938228 modified "2023-10-16" @default.
- W4386938228 title "A Transformer-Based Framework for Biomedical Information Retrieval Systems" @default.
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- W4386938228 doi "https://doi.org/10.1007/978-3-031-44223-0_26" @default.
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