Full
Outline
To construct a nursing knowledge question answering system based on deep learning technology and to evaluate its application effectiveness in clinical nursing.
A knowledge base in the nursing domain was constructed using deep learning methods.The pre-trained language models was taken such as Bidirectional encoder representations from transformers(BERT) as the core to develop the nursing knowledge question answering system.The technical performance and clinical application effects of the system were evaluated.
The constructed nursing knowledge question answering system achieved an accuracy of 86.8% on nursing professional questions.The average response time was 1.2 seconds.Clinical application results showed that the system effectively reduced the workload of nurses.The per shift time spent for patients' answering common questions in nurses was decreased by 93.4%.The satisfaction score of the nurse was 4.3.
The nursing knowledge question answering system based on deep learning can effectively enhance nursing work efficiency and provide reliable knowledge support for nurses.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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