Survey of Awareness of Artificial Intelligence in Diabetes Care Among Endocrinologists in Malaysia
https://doi.org/10.15605/jafes.041.S1
- Author:
Jia Miin Sun
1
;
Chee Keong See
1
Author Information
1. Hospital Sultan Haji Ahmad Shah
- Publication Type:Journal Article
- MeSH:
Artificial Intelligence;
Endocrinologists;
Malaysia;
Diabetes Mellitus
- From:
Journal of the ASEAN Federation of Endocrine Societies
2026;41(S1):48-
- CountryPhilippines
- Language:English
-
Abstract:
Introduction:Artificial intelligence (AI) and digital health technologies
are increasingly integrated into diabetes care. However,
data on awareness and adoption among endocrinologists
in Malaysia remain limited.
Methodology:A cross-sectional survey was conducted among endocrinologists in Malaysia using a structured online questionnaire.
Items assessed awareness of AI-based diabetes technologies,
attitudes toward AI in clinical care, perceived barriers, and
willingness to adopt AI tools. Multiple responses were
permitted for selected items.
Results:The cohort (N = 65) comprised 60% junior endocrinologists
and 40% senior endocrinologists (72% governmentbased). Recognition was higher for monitoring and
screening technologies, particularly continuous glucose
monitoring (CGM) data analytics (66.2%) and automated
retinopathy screening (33.8%) versus therapeutic AI tools,
such as lifestyle coaching applications (43.1%) and insulin
titration algorithms (30.8%). While approximately 60%
endocrinologists reported familiarity with AI in diabetes
care, 15.4% of them had no prior recognition of AI tools.
Attitudes toward AI were largely positive; 76% agreed
that AI improves diabetes outcomes, 60% believed it
reduces clinician workload, and 90% agreed that AI would
complement diabetes care systems. However, approximately 50% remained neutral regarding its reliability and
expressed concerns about ethics and data security.
In practice, only 40% endocrinologists reported using AI
tools, most commonly CGM analytics with automated
insights (46.4%), with generally low frequency of use. The
main barriers to adoption were lack of formal training
(78.5%) and high implementation costs (60%). Despite this,
90% expressed willingness to adopt AI in future practice.
Conclusion:Awareness of AI technologies in diabetes care among
Malaysian endocrinologists is variable, with stronger
recognition of tools already embedded in routine practice.
While attitudes toward AI are favorable, significant
educational and structural barriers must be addressed to
facilitate broader implementation.
- Full text:202607301135420299EP_A052.pdf
