AIMC Topic: China

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Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy.

Theranostics
Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothes...

Development and validation of a questionnaire to assess public receptivity toward autonomous vehicles and its relation with the traffic safety climate in China.

Accident; analysis and prevention
The advent of autonomous vehicles (AVs) has gained increasing attention in China. Although auto manufacturers and innovators have attempted to confirm that AVs are safe and have introduced them on public roads, it is vital to understand end-users' ac...

A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: The Named Entity Recognition (NER) task as a key step in the extraction of health information, has encountered many challenges in Chinese Electronic Medical Records (EMRs). Firstly, the casual use of Chinese abbreviations and doctors' per...

Applying deep matching networks to Chinese medical question answering: a study and a dataset.

BMC medical informatics and decision making
BACKGROUND: Medical and clinical question answering (QA) is highly concerned by researchers recently. Though there are remarkable advances in this field, the development in Chinese medical domain is relatively backward. It can be attributed to the di...

A fine-grained Chinese word segmentation and part-of-speech tagging corpus for clinical text.

BMC medical informatics and decision making
BACKGROUND: Chinese word segmentation (CWS) and part-of-speech (POS) tagging are two fundamental tasks of Chinese text processing. They are usually preliminary steps for lots of Chinese natural language processing (NLP) tasks. There have been a large...

A hybrid approach for named entity recognition in Chinese electronic medical record.

BMC medical informatics and decision making
BACKGROUND: With the rapid spread of electronic medical records and the arrival of medical big data era, the application of natural language processing technology in biomedicine has become a hot research topic.

On building a diabetes centric knowledge base via mining the web.

BMC medical informatics and decision making
BACKGROUND: Diabetes has become one of the hot topics in life science researches. To support the analytical procedures, researchers and analysts expend a mass of labor cost to collect experimental data, which is also error-prone. To reduce the cost a...

Attention-based deep residual learning network for entity relation extraction in Chinese EMRs.

BMC medical informatics and decision making
BACKGROUND: Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of clinical texts, resulting in...

Entity recognition in Chinese clinical text using attention-based CNN-LSTM-CRF.

BMC medical informatics and decision making
BACKGROUND: Clinical entity recognition as a fundamental task of clinical text processing has been attracted a great deal of attention during the last decade. However, most studies focus on clinical text in English rather than other languages. Recent...

Research on soil moisture prediction model based on deep learning.

PloS one
Soil moisture is one of the main factors in agricultural production and hydrological cycles, and its precise prediction is important for the rational use and management of water resources. However, soil moisture involves complex structural characteri...