马来西亚医科大学生对人工智能的准备情况

Pang Yi Xuan, Mohamed Ismath Fathima Fahumida, Muhammad Imran Al Nazir Hussain, Nethmi Thathsarani Jayathilake, Sujata Khobragade, H. Soe, S. Moe, M. Htay
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引用次数: 1

摘要

人工智能(AI)技术正在快速发展,并渗透到人们日常生活的许多方面。医学生对医学领域人工智能的倾向增加了人工智能成功应用的概率及其在医学领域的价值。本研究旨在评估医科本科生的医疗人工智能准备情况。横断面研究于2022年3月至2022年4月在马来西亚一家私人医疗机构进行。采用非概率目的抽样方法招收学生,并通过谷歌表格在线发放调查问卷。使用题为“医学生医学人工智能准备程度量表(MAIRS-MS)”的问卷进行数据收集。分析包括频率表、百分比、标准差、非配对t检验和方差分析(ANOVA)检验。在105名参与者中,67.62%的人得分为53至83分,其次是24.76%的人得分为84至114分,7.62%的人得分为22至52分。获得的医疗人工智能准备度总分均值为75.04分。年龄和学习年份与医疗人工智能准备的能力、视野和伦理领域之间存在显著相关性。之前的训练与医疗人工智能准备的所有四个领域之间存在显著关联。决策者和教育部门应该建立更多的人工智能培训中心,提供和介绍人工智能的基础课程。应该为更年轻的人群提供更多的人工智能课程,让他们更早地接触人工智能数字信息,从而使他们在未来与人工智能技术互动时获得更多的信心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Readiness Towards Artificial Intelligence Among Undergraduate Medical Students in Malaysia
Artificial intelligence (AI) technology is growing at a fast pace and permeates many aspects of people’s daily lives. Medical students’ inclination towards AI in the medical field increases the probability of successful AI adoption and its value in the medical field. This study was conducted to evaluate medical AI readiness among undergraduate medical students. A cross-sectional study was conducted from March 2022 to April 2022 in a private medical institution in Malaysia. A non-probability purposive sampling method was used to enroll students and a questionnaire was distributed online via Google Forms. The questionnaire, captioned “Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS)”, was used for data collection. The analysis included frequency tables, percentages, standard deviation, unpaired t-test, and analysis of variance (ANOVA) test. Out of 105 participants, 67.62% scored 53 to 83, followed by 24.76%, who scored 84 to 114, and 7.62%, who scored 22 to 52 on the medical AI readiness scale. The mean of the total score of medical AI readiness obtained was 75.04. There were significant correlations between age and study year with the ability, vision, and ethics domains of medical AI readiness. A significant association was observed between previous training with all four domains of medical AI readiness. Policymakers and the educational sector should set up more AI training centers to provide and introduce basic courses on AI. More AI courses should be provided to younger populations to engage in AI digital information earlier, thus enabling them to acquire more confidence in interacting with AI technology in the future.
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