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
  • [41] An empirical study of AI-assisted teaching method in music education based on multiple intelligences theory
    Department of Education, Zhengzhou College of Finance and Economics, Henan, Zhengzhou
    450000, China
    Appl. Math. Nonlinear Sci., 2024, 1
  • [42] Patient Data Sharing for AI: Ethical Challenges, Catholic Solutions
    Baric-Parker, Jean
    Anderson, Emily E.
    LINACRE QUARTERLY, 2020, 87 (04): : 471 - 481
  • [43] Performance of three artificial intelligence (AI)-based large language models in standardized testing; implications for AI-assisted dental education
    Sabri, Hamoun
    Saleh, Muhammad H. A.
    Hazrati, Parham
    Merchant, Keith
    Misch, Jonathan
    Kumar, Purnima S.
    Wang, Hom-Lay
    Barootchi, Shayan
    JOURNAL OF PERIODONTAL RESEARCH, 2025, 60 (02) : 121 - 133
  • [44] Pediatric kidney transplantation in Dubai. Outcomes and challenges.
    Mohamed, Marwa
    Alghraizat, Abdalazeez
    Awad, Hazem
    Yamin, Haneen
    Habeeb, Shameer
    Simkova, Eva
    Alhammadi, Entesar
    Eid, Loai
    Concepcion, Waldo
    Bitzan, Martin
    TRANSPLANTATION, 2024, 108 (9S)
  • [45] Accuracy, satisfaction, and impact of custom GPT in acquiring clinical knowledge: Potential for AI-assisted medical education
    Pu, Jiaxi
    Hong, Jie
    Yu, Qiao
    Yu, Pan
    Tian, Jiaqi
    He, Yuehua
    Huang, Hanwei
    Yuan, Qiongjing
    Tao, Lijian
    Peng, Zhangzhe
    MEDICAL TEACHER, 2025,
  • [46] IDENTIFICATION OF MEANINGFUL ASPECTS OF PHYSICAL ACTIVITY: CONCEPT ELICITATION BY AI-ASSISTED CODING OF ONLINE PATIENT CONVERSATIONS
    Bridges, Y.
    Chowdhury, M.
    Tahsin, A.
    Bessant, C.
    Abdollahyan, M.
    Smeraldi, F.
    Byrom, B.
    VALUE IN HEALTH, 2022, 25 (01) : S226 - S226
  • [47] Optimizing Patient Care Pathways: Impact Analysis of an AI-Assisted Smart Referral System for Musculoskeletal Services
    Raza, Haider
    Rathee, Dheeraj
    Amorim, Renato
    Fasli, Maria
    2024 IEEE INTERNATIONAL CONFERENCE ON DIGITAL HEALTH, ICDH 2024, 2024, : 68 - 72
  • [48] Developing an AI-assisted clinical decision support system to enhance in-patient holistic health care
    Juang, Wang-Chuan
    Hsu, Ming-Hsia
    Cai, Zheng-Xun
    Chen, Chia-Mei
    PLOS ONE, 2022, 17 (10):
  • [49] AI-Assisted X-ray Fracture Detection in Residency Training: Evaluation in Pediatric and Adult Trauma Patients
    Meetschen, Mathias
    Salhoefer, Luca
    Beck, Nikolas
    Kroll, Lennard
    Ziegenfuss, Christoph David
    Schaarschmidt, Benedikt Michael
    Forsting, Michael
    Mizan, Shamoun
    Umutlu, Lale
    Hosch, Rene
    Nensa, Felix
    Haubold, Johannes
    DIAGNOSTICS, 2024, 14 (06)
  • [50] TECHNICAL CHALLENGES IN LIVING DONOR KIDNEY TRANSPLANTATION - DIAGNOSIS AND SOLUTIONS
    Dziodzio, T.
    Alqasim, K.
    Ritschl, P.
    Klein, F.
    Raschzok, N.
    Jara, M.
    Gerlach, U.
    Chopra, S.
    Schmelzle, M.
    Otto, N.
    Reinke, P.
    Pratschke, J.
    Oellinger, R.
    TRANSPLANT INTERNATIONAL, 2018, 31 : 19 - 19