… Recent studies in the biomedical domain incorporate expert-… for disambiguation of biomedical
text data, a deep learning–… and biomedical specific features were used for WSD evaluation…

… Word sense disambiguation is a core research field in … of artificial intelligence and machine
learning scientists and the … Word Sense Disambiguation in the biomedical domain through …

… In recent years, deep learning methods have been applied to … However, in the biomedical
domain, they have not out-… As as result, our training and evaluating were performed on the …

… A wide range of Word Sense Disambiguation (WSD) … Sense disambiguation methods in the
biomedical domain … benchmark combinations from a unified evaluation framework [40] that is …

… Zhang proposes two supervised WSD models based on deep learning technology [6]. One …
WSD in biomedical domain is evaluated. Cao proposes an enhanced deep clustering network…

… Liu applies 3 machine learning algorithms to biomedical WSD, including Naive Bayes and …
evaluated [24]. Yepes compares 4 knowledge-based WSD methods in the biomedical domain…

… diverse approaches ranging from deep learning techniques to … of neural networks for
biomedical text disambiguation, from … Uncertainty evaluation is critical in various machine learning …

… evaluation results show that it outperforms most of the knowledge-based methods for WSD in
the biomedical domain… effective deep neural word sense disambiguation of biomedical text …

… "ambiguous words," and the method of evaluating the proper … in existence during this whole
domain; these studies were … Disambiguating ambiguous biomedical terms in biomedical …

… ) by testing traditional supervised machine learning algorithms … we will review the clinical
abbreviation disambiguation task as … biomedical corpora which are used in the clinical domain: …