Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
versions View all 3 versions
addClaim

Knowledge, attitude, and practice of artificial intelligence (AI) among medical students: A cross-sectional study from Ipoh, Perak

Authors: Qin, Kam Xoong; Ahmad, Nameera; Soomro, Kinza; Yogaiswaaran, Shedu; Singogo, Taonga Dora; Rasheed, Ali Jumah;

Knowledge, attitude, and practice of artificial intelligence (AI) among medical students: A cross-sectional study from Ipoh, Perak

Abstract

ABSTRACT Introduction: Artificial intelligence (AI), replicates human intelligence, is increasingly gaining attention in higher education to address traditional educational challenges. AI offers vast potential for implementation in pathology, cardiology, radiology, and dermatology. Its potential to revolutionise the current medical practices in these areas is significant. This study aims to explore the knowledge, attitude, and practice (KAP) of AI among medical students at Quest International University in Malaysia. Methods: A cross-sectional descriptive study was conducted at the Faculty of Medicine, Quest International University (QIU) from January 2024 to March 2024. A structured questionnaire was distributed among the medical students of QIU, where 53 students responded to the questionnaire and participated in this research. Results: All students had an idea about AI, but only 54.7% were aware of the subtype classification of AI. Regarding the AI application in medical fields, radiology, and Pathology, the vast majority were unaware 73.6%, 71.7%, and 73.6% respectively. Indians have significantly good knowledge compared to other ethnicities [Chi(df) = 12.95 (4), P value = 0.005]. Second year students have relatively good knowledge. The majority of the students agreed upon the essentiality 48(90.6%), inclusion of AI in the medical school curriculum and specialist training 44(83%), early diagnosis and disease assessment 40(75.5%), AI essentiality in radiology 36(67.9%), Pathology 38(71.7%). Conclusion: There is a need for training in AI which will improve the knowledge of AI and influence their attitudes towards using it in medicine. Achieving widespread and flawless AI in medicine is challenging, but a collaborative effort between education institutions and government organisations may help improve the scenario.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average