Mapping layperson medical terminology into the Human Phenotype Ontology using neural machine translation models-Reference-Cited by-同舟云学术

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Mapping layperson medical terminology into the Human Phenotype Ontology using neural machine translation models

Published:2022-10 Issue: Volume:204 Page:117446
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Manzini Enrico,Garrido-Aguirre Jon^ORCID,Fonollosa Jordi^ORCID,Perera-Lluna Alexandre^ORCID

Funder

European Commission

Gobierno de España Ministerio de Economía y Competitividad

ACCIÓ

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference38 articles.

1. Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors;Baroni,2014

2. Using cooccurrence statistics and the web to discover synonyms in a technical language;Baroni,2004

3. Keras;Chollet,2015

4. Indexing by latent semantic analysis;Deerwester;Journal of the American Society for Information Science,1990

5. Domain-specific language model pretraining for biomedical natural language processing;Gu;ACM Transactions on Computing for Healthcare,2022

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Explanatory argumentation in natural language for correct and incorrect medical diagnoses;Journal of Biomedical Semantics;2024-05-30

2. Adopting machine translation in the healthcare sector: A methodological multi-criteria review;Computer Speech & Language;2024-03

3. A text style transfer system for reducing the physician–patient expertise gap: An analysis with automatic and human evaluations;Expert Systems with Applications;2023-12

4. Synset2Node: A new synset embedding based upon graph embeddings;Intelligent Systems with Applications;2023-02

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