https://scholars.lib.ntu.edu.tw/handle/123456789/595336
標題: | Modified Bidirectional Encoder Representations From Transformers Extractive Summarization Model for Hospital Information Systems Based on Character-Level Tokens (AlphaBERT): Development and Performance Evaluation | 作者: | YEN-PIN CHEN Chen, Yi-Ying CHIEN-HUA HUANG JR-JIUN LIN FEI-PEI LAI |
關鍵字: | BERT; automatic summarization; deep learning; emergency medicine; transformer | 公開日期: | 29-四月-2020 | 出版社: | JMIR PUBLICATIONS, INC | 卷: | 8 | 期: | 4 | 來源出版物: | JMIR medical informatics | 摘要: | Doctors must care for many patients simultaneously, and it is time-consuming to find and examine all patients' medical histories. Discharge diagnoses provide hospital staff with sufficient information to enable handling multiple patients; however, the excessive amount of words in the diagnostic sentences poses problems. Deep learning may be an effective solution to overcome this problem, but the use of such a heavy model may also add another obstacle to systems with limited computing resources. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/595336 | ISSN: | 2291-9694 | DOI: | 10.2196/17787 |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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