The World Health Organization (WHO) has responded to the 2011 East-Japan earthquake and tsunami through the three levels of its decentralised structure. It has provided public health advice regarding a number of issues relating to protective measures, potassium iodide use, as well as safety of food and drinking water, mental health, travel, tourism, and trade. WHO is currently developing an initial health risk assessment linked to a preliminary evaluation of radiation exposure around the world from the Fukushima Daiichi nuclear accident. Lessons learned from this disaster are likely to help future emergency response to multi-faceted disasters.
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| http://dx.doi.org/10.1088/0952-4746/32/1/N119 | DOI Listing |
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In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
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