Evaluation of Machine Translation Accuracy Focused on the Adverse Event Terminology for Medical Devices

被引：0

作者：

Yagahara, Ayako ^{[1
]}

Uesugi, Masahito ^{[2
]}

Yokoi, Hideto ^{[3
]}

机构：

[1] Hokkaido Univ Sci, Sapporo, Hokkaido, Japan

[2] Hokkaido Informat Univ, Ebetsu, Hokkaido, Japan

[3] Kagawa Univ Hosp, Miki, Kagawa, Japan

来源：

MEDINFO 2023 - THE FUTURE IS ACCESSIBLE | 2024年 / 310卷

关键词：

Medical device adverse event; neural machine translation; terminology;

D O I：

10.3233/SHTI231239

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The purpose of this study was to evaluate the accuracy of deep neural machine translation focused on medical device adverse event terminology. 10 models were obtained, and their English-to-Japanese translation accuracy was evaluated using quantitative and qualitative measures. No significant difference was found in the quantitative index except for a few pairs. In the qualitative evaluation, there was a significant difference and googletrans and GPT-3 were regarded as useful models.

引用

页码：1450 / 1451

页数：2

共 30 条

[1] Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL
Yagahara, Ayako
Yokoi, Hideto
[J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2022, 22 (01)
[2] Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL
Ayako Yagahara
Hideto Yokoi
[J]. BMC Medical Informatics and Decision Making, 22
[3] Evaluation of Similar Term Definitions in Medical Device Adverse Event Terminology
Yagahara, Ayako
Uesugi, Masahito
Yokoi, Hideto
[J]. MEDINFO 2019: HEALTH AND WELLBEING E-NETWORKS FOR ALL, 2019, 264 : 1620 - 1621
[4] GENDER DISPARITIES IN ADVERSE EVENT REPORTING FOR MEDICAL DEVICES
Pierce, Hudson
Ahsan, Muhammad
Goel, Shokhi
Asfaw, Tirsit
Anger, Jennifer
Chughtai, Bilal
[J]. JOURNAL OF UROLOGY, 2020, 203 : E1256 - E1257
[5] Implementation of adverse event reporting for medical devices, India
Shukla, Shatrunajay
Gupta, Madhur
Pandit, Sabitri
Thomson, Milu
Shivhare, Abhimanyu
Kalaiselvan, Vivekanandan
Singh, Gyanendra Nath
[J]. BULLETIN OF THE WORLD HEALTH ORGANIZATION, 2020, 98 (03) : 206 - 211
[6] Improving FDA postmarket adverse event reporting for medical devices
Wunnava, Susmitha
Miller, Timothy A.
Bourgeois, Florence T.
[J]. BMJ EVIDENCE-BASED MEDICINE, 2023, 28 (02) : 83 - 84
[7] Identification of Synonyms Using Definition Similarities in Japanese Medical Device Adverse Event Terminology
Yagahara, Ayako
Uesugi, Masahito
Yokoi, Hideto
[J]. APPLIED SCIENCES-BASEL, 2021, 11 (08):
[8] Evaluation of the Validity of Back-Translation as a Method of Assessing the Accuracy of Machine Translation
Miyabe, Mai
Yoshino, Takashi
[J]. 2015 INTERNATIONAL CONFERENCE ON CULTURE AND COMPUTING (CULTURE COMPUTING), 2015, : 145 - 150
[9] Machine translation of standardised medical terminology using natural language processing: A scoping review
Noll, Richard
Frischen, Lena S.
Boeker, Martin
Storf, Holger
Schaaf, Jannik
[J]. NEW BIOTECHNOLOGY, 2023, 77 : 120 - 129
[10] A STANDARDIZED APPROACH TO ADVERSE EVENT TERMINOLOGY IN ABUSE POTENTIAL EVALUATION: THE NEXT ITERATION.
Romach, M.
Sellers, E.
[J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2014, 95 : S62 - S63

← 1 2 3 →