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Integrated Natural Language Processing and Machine Learning Models for Standardizing Radiotherapy Structure Names
2020
Healthcare
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Domain experts identified as anatomically significant nine prostate and ten lung organs-at-risk (OAR) structures and manually labeled them according to the TG-263 standards, and remaining structures were ...
To standardize radiotherapy structure names, we developed an integrated natural language processing (NLP) and machine learning (ML) based system that can map the physician-given structure names to American ...
Machine-learning-based methods are well suited for retrospective structure name relabeling but are seldom used in this domain. ...
doi:10.3390/healthcare8020120
pmid:32365973
pmcid:PMC7348919
fatcat:2e7q3bz7x5enzngl3blofuqnga
Multi-View Data Integration Methods for Radiotherapy Structure Name Standardization
2021
Cancers
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We present novel approaches to integrate complementary types (views) of structure data to build better-performing machine learning models. ...
We present two methods, namely (a) intermediate integration and (b) late integration, to combine physician-given textual structure name features and geometric information of structures. ...
The scikit-learn library for machine learning [17] was used to build the models. ...
doi:10.3390/cancers13081796
pmid:33918716
fatcat:bs5t3opscrgzjg4wsksklgrkw4