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cs.LG2021
Biomedical Data-to-Text Generation via Fine-Tuning Transformers
Ruslan Yermakov, Nicholas Drago, Angelo Ziletti
Data-to-text (D2T) generation in the biomedical domain is a promising - yet mostly unexplored - field of research. Here, we apply neural models for D2T generation to a real-world d…
cs.LG2020
Discovering key topics from short, real-world medical inquiries via natural language processing and unsupervised learning
Angelo Ziletti, Christoph Berns, Oliver Treichel +8
Millions of unsolicited medical inquiries are received by pharmaceutical companies every year. It has been hypothesized that these inquiries represent a treasure trove of informati…