Healthcare students' knowledge, attitudes, and perspectives toward artificial intelligence in the southern Vietnam

被引:5
作者
Truong, Nguyen Minh [1 ]
Vo, Trung Quang [1 ,4 ]
Tran, Hien Thi Bich [1 ]
Nguyen, Hiep Thanh [2 ]
Pham, Van Nu Hanh [3 ]
机构
[1] Pham Ngoc Thach Univ Med, Fac Pharm, Ho Chi Minh City 700000, Vietnam
[2] Pham Ngoc Thach Univ Med, Fac Med, Ho Chi Minh City 700000, Vietnam
[3] Hanoi Univ Pharm, Fac Pharmaceut Management & Econ, Hanoi 100000, Vietnam
[4] 02 Duong Quang Trung St,Ward 12,Dist 10, Ho Chi Minh 700000, Vietnam
关键词
Artificial intelligence; AI; Healthcare student; KAP; Vietnam;
D O I
10.1016/j.heliyon.2023.e22653
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The application of new technologies in medical education still lags behind the extraordinary advances of AI. This study examined the understanding, attitudes, and perspectives of Vietnamese medical students toward AI and its consequences, as well as their knowledge of existing AI operations in Vietnam. A cross-sectional online survey was administered to 1142 students enrolled in undergraduate medicine and pharmacy programs. Most of the participants had no understanding of AI in healthcare (1053 or 92.2 %). The majority believed that AI would benefit their careers (890 or 77.9 %) and that such innovation will be used to oversee public health and epidemic prevention on their behalf (882 or 77.2 %). The proportion of students with satisfactory knowledge significantly differed depending on gender (P < 0.001), major (P = 0.003), experience (P < 0.001), and income (P = 0.011). The percentage of respondents with positive attitudes significantly differed by year level (P = 0.008) and income (P = 0.003), and the proportion with favorable perspectives regarding AI varied considerably by age (P = 0.046) and major (P < 0.001). Most of the participants wanted to integrate AI into radiology and digital imaging training (P = 0.283), while the fifth-year students wished to learn about AI in medical genetics and genomics (P < 0.001, 4.0 +/- 0.8). The male students had 1.898 times more adequate knowledge of AI than their female counterparts, and those who had attended webinars/lectures/courses on AI in healthcare had 4.864 times more adequate knowledge than those having no such experiences. The majority believed that the barrier to implementing AI in healthcare is the lack of financial resources (83.54 %) and appropriate training (81.00 %). Participants saw AI as a "partner" rather than a "competitor", but the majority of low knowledge was recorded. Future research should take into account the way to integrate AI into medical training programs for healthcare students.
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页数:11
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共 61 条
  • [1] Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Pakistan: A cross-sectional online survey
    Ahmed, Zaboor
    Bhinder, Khurram Khaliq
    Tariq, Amna
    Tahir, Muhammad Junaid
    Mehmood, Qasim
    Tabassum, Muhammad Saad
    Malik, Muna
    Aslam, Sana
    Asghar, Muhammad Sohaib
    Yousaf, Zohaib
    [J]. ANNALS OF MEDICINE AND SURGERY, 2022, 76
  • [2] Alugubelli R., 2016, Int J Innovat Eng Res Technol, V3, P1
  • [3] Teacherbot: interventions in automated teaching
    Bayne, Sian
    [J]. TEACHING IN HIGHER EDUCATION, 2015, 20 (04) : 455 - 467
  • [4] Beck, 2016, ARXIV160605718
  • [5] Automated analysis of free speech predicts psychosis onset in high-risk youths
    Bedi G.
    Carrillo F.
    Cecchi G.A.
    Slezak D.F.
    Sigman M.
    Mota N.B.
    Ribeiro S.
    Javitt D.C.
    Copelli M.
    Corcoran C.M.
    [J]. npj Schizophrenia, 1 (1):
  • [6] Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception
    Bisdas, Sotirios
    Topriceanu, Constantin-Cristian
    Zakrzewska, Zosia
    Irimia, Alexandra-Valentina
    Shakallis, Loizos
    Subhash, Jithu
    Casapu, Maria-Madalina
    Leon-Rojas, Jose
    Pinto dos Santos, Daniel
    Andrews, Dilys Miriam
    Zeicu, Claudia
    Bouhuwaish, Ahmad Mohammad
    Lestari, Avinindita Nura
    Abu-Ismail, Lua'i
    Sadiq, Arsal Subbah
    Khamees, Almu'atasim
    Mohammed, Khaled M. G.
    Williams, Estelle
    Omran, Aya Ibrahim
    Ismail, Dima Y. Abu
    Ebrahim, Esraa Hasan
    [J]. FRONTIERS IN PUBLIC HEALTH, 2021, 9
  • [7] Artificial Intelligence in Radiology-Ethical Considerations
    Brady, Adrian P.
    Neri, Emanuele
    [J]. DIAGNOSTICS, 2020, 10 (04)
  • [8] Brandes Gabriela Irene Garcia, 2020, Radiol Bras, V53, P167, DOI 10.1590/0100-3984.2019.0101
  • [9] Implementing Machine Learning in Health Care - Addressing Ethical Challenges
    Char, Danton S.
    Shah, Nigam H.
    Magnus, David
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2018, 378 (11) : 981 - 983
  • [10] Artificial intelligence in medical education: a cross-sectional needs assessment
    Civaner, M. Murat
    Uncu, Yesim
    Bulut, Filiz
    Chalil, Esra Giounous
    Tatli, Abdulhamit
    [J]. BMC MEDICAL EDUCATION, 2022, 22 (01)