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pro vyhledávání: '"Sarma, Prathusha K"'
We study the problem of medical symptoms recognition from patient text, for the purposes of gathering pertinent information from the patient (known as history-taking). A typical patient text is often descriptive of the symptoms the patient is experie
Externí odkaz:
http://arxiv.org/abs/2011.06874
This paper proposes a way to improve the performance of existing algorithms for text classification in domains with strong language semantics. We propose a domain adaptation layer learns weights to combine a generic and a domain specific (DS) word em
Externí odkaz:
http://arxiv.org/abs/1908.06082
This paper learns multi-modal embeddings from text, audio, and video views/modes of data in order to improve upon down-stream sentiment classification. The experimental framework also allows investigation of the relative contributions of the individu
Externí odkaz:
http://arxiv.org/abs/1907.08696
Generic word embeddings are trained on large-scale generic corpora; Domain Specific (DS) word embeddings are trained only on data from a domain of interest. This paper proposes a method to combine the breadth of generic embeddings with the specificit
Externí odkaz:
http://arxiv.org/abs/1805.04576
Autor:
Kornfield, Rachel, Sarma, Prathusha K, Shah, Dhavan V, McTavish, Fiona, Landucci, Gina, Pe-Romashko, Klaren, Gustafson, David H
Publikováno v:
Journal of Medical Internet Research
Background: Online discussion forums allow those in addiction recovery to seek help through text-based messages, including when facing triggers to drink or use drugs. Trained staff (or “moderators”) may participate within these forums to offer gu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15a3c678e092331b1baa60aba4f77491
https://doi.org/10.2196/preprints.10136.a
https://doi.org/10.2196/preprints.10136.a
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