NLP-derived attributes from construction incident reports remain strongly predictive of independently labeled safety outcomes even after removing potential label leakage, with injury severity now well predicted on a dataset of more than 90,000 reports.
Notes on Deep Learning for NLP
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
abstract
My notes on Deep Learning for NLP.
years
2019 2verdicts
UNVERDICTED 2representative citing papers
Standard NLP classifiers can surface valid injury precursors from raw construction safety reports.
citing papers explorer
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AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes
NLP-derived attributes from construction incident reports remain strongly predictive of independently labeled safety outcomes even after removing potential label leakage, with injury severity now well predicted on a dataset of more than 90,000 reports.
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Automatically Learning Construction Injury Precursors from Text
Standard NLP classifiers can surface valid injury precursors from raw construction safety reports.