Impact of automatic query generation and quality recognition using deep learning to curate evidence from biomedical literature: Empirical study

Muhammad Afzal; Maqbool Hussain; Khalid Mahmood Malik; Sungyoung Lee

doi:10.2196/13430

Impact of automatic query generation and quality recognition using deep learning to curate evidence from biomedical literature: Empirical study

Muhammad Afzal
, Maqbool Hussain
, Khalid Mahmood Malik
, Sungyoung Lee^*

^*Corresponding author for this work

Sejong University
Oakland University
Kyung Hee University

Research output: Contribution to journal › Article › peer-review

10 Citations (SciVal)

Original language	English
Article number	e13430
Journal	JMIR Medical Informatics
Volume	7
Issue number	4
DOIs	https://doi.org/10.2196/13430
Publication status	Published (VoR) - 1 Oct 2019

Funding

This research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center support program (IITP-2017-0-01629) supervised by the Institute of Information & Communications Technology Planning & Evaluation (IITP). This work was supported by an IITP grant funded by the Korean government (MSIT; no 2017-0-00655).

Keywords

Biomedical research
Clinical decision support systems
Data curation
Deep learning
Evidence-based medicine
Machine learning
Precision medicine

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10.2196/13430

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title = "Impact of automatic query generation and quality recognition using deep learning to curate evidence from biomedical literature: Empirical study",

keywords = "Biomedical research, Clinical decision support systems, Data curation, Deep learning, Evidence-based medicine, Machine learning, Precision medicine",

author = "Muhammad Afzal and Maqbool Hussain and Malik, \{Khalid Mahmood\} and Sungyoung Lee",

note = "Funding Information: This research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center support program (IITP-2017-0-01629) supervised by the Institute of Information \& Communications Technology Planning \& Evaluation (IITP). This work was supported by an IITP grant funded by the Korean government (MSIT; no 2017-0-00655). Publisher Copyright: {\textcopyright}Muhammad Afzal, Maqbool Hussain, Khalid Mahmood Malik, Sungyoung Lee.",

year = "2019",

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doi = "10.2196/13430",

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T1 - Impact of automatic query generation and quality recognition using deep learning to curate evidence from biomedical literature

T2 - Empirical study

AU - Afzal, Muhammad

AU - Hussain, Maqbool

AU - Malik, Khalid Mahmood

AU - Lee, Sungyoung

N1 - Funding Information: This research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center support program (IITP-2017-0-01629) supervised by the Institute of Information & Communications Technology Planning & Evaluation (IITP). This work was supported by an IITP grant funded by the Korean government (MSIT; no 2017-0-00655). Publisher Copyright: ©Muhammad Afzal, Maqbool Hussain, Khalid Mahmood Malik, Sungyoung Lee.

PY - 2019/10/1

Y1 - 2019/10/1

KW - Biomedical research

KW - Clinical decision support systems

KW - Data curation

KW - Deep learning

KW - Evidence-based medicine

KW - Machine learning

KW - Precision medicine

UR - https://www.scopus.com/pages/publications/85097178852

UR - https://www.scopus.com/pages/publications/85097178852#tab=citedBy

U2 - 10.2196/13430

DO - 10.2196/13430

M3 - Article

AN - SCOPUS:85097178852

SN - 2291-9694

VL - 7

JO - JMIR Medical Informatics

JF - JMIR Medical Informatics

IS - 4

M1 - e13430

ER -

Impact of automatic query generation and quality recognition using deep learning to curate evidence from biomedical literature: Empirical study

Funding

Keywords

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