https://scholars.lib.ntu.edu.tw/handle/123456789/595336
Title: | Modified Bidirectional Encoder Representations From Transformers Extractive Summarization Model for Hospital Information Systems Based on Character-Level Tokens (AlphaBERT): Development and Performance Evaluation | Authors: | YEN-PIN CHEN Chen, Yi-Ying CHIEN-HUA HUANG JR-JIUN LIN FEI-PEI LAI |
Keywords: | BERT; automatic summarization; deep learning; emergency medicine; transformer | Issue Date: | 29-Apr-2020 | Publisher: | JMIR PUBLICATIONS, INC | Journal Volume: | 8 | Journal Issue: | 4 | Source: | JMIR medical informatics | Abstract: | 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 |
Appears in Collections: | 醫學院附設醫院 (臺大醫院) |
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