Efficient Machine Reading Comprehension for Health Care Applications: Algorithm Development and Validation of a Context Extraction Approach
BackgroundExtractive methods for machine reading comprehension (MRC) tasks have achieved comparable or better accuracy than human performance on benchmark data sets. However, such models are not as successful when adapted to complex domains such as health care. One of the mai...
Main Authors: | Duy-Anh Nguyen, Minyi Li, Gavin Lambert, Ryszard Kowalczyk, Rachael McDonald, Quoc Bao Vo |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2024-03-01
|
Series: | JMIR Formative Research |
Online Access: | https://formative.jmir.org/2024/1/e52482 |
Similar Items
-
Improved Machine Reading Comprehension Using Data Validation for Weakly Labeled Data
by: Yunyeong Yang, et al.
Published: (2020-01-01) -
Enhancing Lexical-Based Approach With External Knowledge for Vietnamese Multiple-Choice Machine Reading Comprehension
by: Kiet Van Nguyen, et al.
Published: (2020-01-01) -
Review of Conversational Machine Reading Comprehension
by: LI Kun, LI Yanling, LIN Min
Published: (2021-09-01) -
Read-All-in-Once (RAiO): Multi-Layer Contextual Architecture for Long-Text Machine Reading Comprehension
by: Tuan-Anh Phan, et al.
Published: (2023-01-01) -
English in context : reading comprehension for science and technology /
by: 465455 Saslow, Joan M., et al.
Published: (1985)