AI-assisted patient education: Challenges and solutions in pediatric kidney transplantation

被引:0
|
作者
Ihsan, M. Z.
Apriatama, Dony [1 ,2 ]
Pithriani [3 ]
Amalia, Riza
机构
[1] Univ Palangka Raya, Guidance & Counseling, Palangka Raya, Indonesia
[2] Univ Negeri Malang, Guidance & Counseling, Malang, Indonesia
[3] Inst Agama Islam Negeri Palangkaraya, Islamic Educ Management, Palangka Raya, Indonesia
关键词
Artificial Intelligence (AI); Patient Education; Pediatric Kidney Transplantation; Healthcare Communication; ChatGPT;
D O I
10.1016/j.pec.2024.108575
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
We are writing in response to the recent publication on the use of artificial intelligence, particularly ChatGPT, in generating educational materials for pediatric kidney transplant patients (Patient Education and Counseling, Volume 129, 2024). The study offers valuable insights into AI's potential to enhance healthcare communication and patient education, specifically by streamlining the creation of materials for caregivers, adolescents, and children facing complex medical procedures[1]. As researchers working at the intersection of healthcare and technology, we would like to offer further reflections on the study's findings, providing both constructive feedback and innovative solutions for advancing the use of AI in this field. One of the most compelling aspects of the study is the potential for ChatGPT to revolutionize patient education by significantly reducing the time and resources needed to develop educational content. The authors demonstrated that even a free version of ChatGPT allows healthcare providers to rapidly generate materials, which is particularly advantageous for overstretched healthcare systems. Additionally, the study highlights ChatGPT's ability to bridge communication gaps in resource-limited settings by providing patients and families with accessible, personalized information about transplant procedures. We strongly support the idea that AI-driven education can democratize access to essential health information, especially in regions where medical expertise is limited. Furthermore, AI's real-time response capabilities could enable healthcare providers to offer more interactive and tailored education, empowering patients to make informed decisions about their health.
引用
收藏
页数:2
相关论文
共 50 条
  • [11] AI-Assisted Writing in Education: Ecosystem Risks and Mitigations
    Shibani, Antonette
    Shum, Simon Buckingham
    PROCEEDINGS OF THE THIRD WORKSHOP ON INTELLIGENT AND INTERACTIVE WRITING ASSISTANTS, IN2WRITING 2024, 2024, : 4 - 6
  • [12] Artificial Intelligence Serves Legal Education: The Application and Challenges of Chinese AI-assisted Judicial Trials
    Bi, Fan
    Yu, Xiong
    Chen, Zhaoying
    Xu, Mingyue
    Xiao, Kun
    INTERNATIONAL JOURNAL OF MULTIPHYSICS, 2024, 18 (03) : 140 - 149
  • [13] Pediatric Kidney Transplantation in the Middle-East: Challenges and Solutions
    Saeed, Bassam
    TRANSPLANTATION, 2022, 106 (09) : S702 - S702
  • [14] AI-Assisted Enhancement of Student Presentation Skills: Challenges and Opportunities
    Chen, Julia
    Lai, Pauli
    Chan, Aulina
    Man, Vicky
    Chan, Chi-Ho
    SUSTAINABILITY, 2023, 15 (01)
  • [15] Work in Progress: An AI-Assisted Metaverse for Computer Science Education
    Ho, Kin-Hon
    Hou, Yun
    Chu, Chun Fai Carlin
    Chan, Chi-Kong
    Pan, Haoyuan
    Chan, Tse-Tin
    2023 IEEE WORLD ENGINEERING EDUCATION CONFERENCE, EDUNINE, 2023,
  • [16] AI-assisted Synthesis in Next Generation EDA: Promises, Challenges, and Prospects
    Wu, Nan
    Xie, Yuan
    Hao, Cong
    2022 IEEE 40TH INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD 2022), 2022, : 207 - 214
  • [17] Digital transformation in engineering education: Exploring the potential of AI-assisted learning
    Pham, Thanh
    Nguyen, Binh
    Ha, Son
    Ngoc, Thanh Nguyen
    AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY, 2023, 39 (05) : 1 - 19
  • [18] Digital Transition Framework for Higher Education in AI-Assisted Engineering Teaching
    Zhang, Yin
    Zhang, Menglong
    Wu, Liming
    Li, Jin
    SCIENCE & EDUCATION, 2025, 34 (02) : 933 - 954
  • [19] Towards Accountable and Resilient AI-Assisted Networks: Case Studies and Future Challenges
    Wang, Shen
    Sandeepa, Chamara
    Senevirathna, Thulitha
    Siniarski, Bartlomiej
    Manh-Dung Nguyen
    Marchal, Samuel
    Liyanage, Madhusanka
    2024 JOINT EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS & 6G SUMMIT, EUCNC/6G SUMMIT 2024, 2024, : 818 - 823
  • [20] Bridging the experience gap in pediatric radiology: towards AI-assisted diagnosis for children
    Somasundaram, Elanchezhian
    Meyers, Arthur B.
    PEDIATRIC RADIOLOGY, 2023, 53 (12) : 2398 - 2399