TY - JOUR
T1 - Global Research Trends of Gender-Related Artificial Intelligence in Medicine Between 2001–2020
T2 - A Bibliometric Study
AU - Yoon, Ha Young
AU - Lee, Heisook
AU - Yee, Jeong
AU - Gwak, Hye Sun
N1 - Funding Information:
The research leading to these results received funding from Ministry of Science and ICT under WISET202103GI01.
Publisher Copyright:
Copyright © 2022 Yoon, Lee, Yee and Gwak.
PY - 2022/5/17
Y1 - 2022/5/17
N2 - This study aimed to assess the research on medical Artificial intelligence (AI) related to sex/gender and explore global research trends over the past 20 years. We searched the Web of Science (WoS) for gender-related medical AI publications from 2001 to 2020. We extracted the bibliometric data and calculated the annual growth of publications, Specialization Index, and Category Normalized Citation Impact. We also analyzed the publication distributions by institution, author, WoS subject category, and journal. A total of 3,110 papers were included in the bibliometric analysis. The number of publications continuously increased over time, with a steep increase between 2016 and 2020. The United States of America and Harvard University were the country and institution that had the largest number of publications. Surgery and urology nephrology were the most common subject categories of WoS. The most occurred keywords were machine learning, classification, risk, outcomes, diagnosis, and surgery. Despite increased interest, gender-related research is still low in medical AI field and further research is needed.
AB - This study aimed to assess the research on medical Artificial intelligence (AI) related to sex/gender and explore global research trends over the past 20 years. We searched the Web of Science (WoS) for gender-related medical AI publications from 2001 to 2020. We extracted the bibliometric data and calculated the annual growth of publications, Specialization Index, and Category Normalized Citation Impact. We also analyzed the publication distributions by institution, author, WoS subject category, and journal. A total of 3,110 papers were included in the bibliometric analysis. The number of publications continuously increased over time, with a steep increase between 2016 and 2020. The United States of America and Harvard University were the country and institution that had the largest number of publications. Surgery and urology nephrology were the most common subject categories of WoS. The most occurred keywords were machine learning, classification, risk, outcomes, diagnosis, and surgery. Despite increased interest, gender-related research is still low in medical AI field and further research is needed.
KW - artificial intelligence
KW - bibliometric analysis
KW - gender
KW - medical research
KW - medicine
UR - http://www.scopus.com/inward/record.url?scp=85130881241&partnerID=8YFLogxK
U2 - 10.3389/fmed.2022.868040
DO - 10.3389/fmed.2022.868040
M3 - Article
AN - SCOPUS:85130881241
VL - 9
JO - Frontiers in Medicine
JF - Frontiers in Medicine
SN - 2296-858X
M1 - 868040
ER -