Evaluation of word embedding models to extract and predict surgical data in breast cancer

Evaluation of word embedding models to extract and predict surgical data in breast cancer

Abstract Background Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated Delphi surveys investigate experts' opi...

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Bibliographic Details
Main Authors: Giuseppe Sgroi, Giulia Russo, Anna Maglia, Giuseppe Catanuto, Peter Barry, Andreas Karakatsanis, Nicola Rocco, ETHOS Working Group, Francesco Pappalardo
Format: Article
Language:English
Published: BMC 2022-11-01
Series:BMC Bioinformatics
Subjects:
Machine learning
Word embeddings
Word2Vec
Breast cancer
Natural language processing
Online Access:https://doi.org/10.1186/s12859-022-05038-6

Internet

https://doi.org/10.1186/s12859-022-05038-6

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