Combining human and <scp>AI</scp> could predict nephrologies future, but should be handled with care

Alhasan, Khalid; Raina, Rupesh; Jamal, Amr; Temsah, Mohamad-Hani

doi:10.1111/apa.16867

Cited by 9 publications

(7 citation statements)

References 11 publications

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“…Similarly, this was observed for radiologist and IT specialists who showed high expectations of AI in the future but low confidence, even they had heterogenous attitudes about incorporating AI in medical education, informing patients about AI use in medical practices [ 53 ]. Therefore, the future challenge lies in determining the appropriate role of AI in medical practice, perhaps to serve as a supplementary tool, rather than replacing human mind [ [54] , [55] , [56] , [57] , [58] ].…”

Section: Discussionmentioning

confidence: 99%

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice

Aljamaan,

Malki,

Alhasan

et al. 2024

Heliyon

Self Cite

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Section: Discussionmentioning

confidence: 99%

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice

Aljamaan,

Malki,

Alhasan

et al. 2024

Heliyon

Self Cite

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“…The high level of interest generated by our study indicates that HCWs are eager to learn more about ChatGPT and other AI Chatbots. ChatGPT was frequently utilized to quickly generate educational materials and provide healthcare advice to patients and communities [ 22 , 23 , 24 ]. Therefore, providing more educational resources and training programs on AI Chatbots could enhance their usability and usefulness in healthcare.…”

Section: Discussionmentioning

confidence: 99%

ChatGPT and the Future of Digital Health: A Study on Healthcare Workers’ Perceptions and Expectations

Temsah,

Aljamaan,

Malki

et al. 2023

Healthcare

Self Cite

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This study aimed to assess the knowledge, attitudes, and intended practices of healthcare workers (HCWs) in Saudi Arabia towards ChatGPT, an artificial intelligence (AI) Chatbot, within the first three months after its launch. We also aimed to identify potential barriers to AI Chatbot adoption among healthcare professionals. A cross-sectional survey was conducted among 1057 HCWs in Saudi Arabia, distributed electronically via social media channels from 21 February to 6 March 2023. The survey evaluated HCWs’ familiarity with ChatGPT-3.5, their satisfaction, intended future use, and perceived usefulness in healthcare practice. Of the respondents, 18.4% had used ChatGPT for healthcare purposes, while 84.1% of non-users expressed interest in utilizing AI Chatbots in the future. Most participants (75.1%) were comfortable with incorporating ChatGPT into their healthcare practice. HCWs perceived the Chatbot to be useful in various aspects of healthcare, such as medical decision-making (39.5%), patient and family support (44.7%), medical literature appraisal (48.5%), and medical research assistance (65.9%). A majority (76.7%) believed ChatGPT could positively impact the future of healthcare systems. Nevertheless, concerns about credibility and the source of information provided by AI Chatbots (46.9%) were identified as the main barriers. Although HCWs recognize ChatGPT as a valuable addition to digital health in the early stages of adoption, addressing concerns regarding accuracy, reliability, and medicolegal implications is crucial. Therefore, due to their unreliability, the current forms of ChatGPT and other Chatbots should not be used for diagnostic or treatment purposes without human expert oversight. Ensuring the trustworthiness and dependability of AI Chatbots is essential for successful implementation in healthcare settings. Future research should focus on evaluating the clinical outcomes of ChatGPT and benchmarking its performance against other AI Chatbots.

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“…During the training process, the model's performance is evaluated and adjusted by partitioning the dataset into training and validation subsets and further enhanced through techniques like transfer learning and fine-tuning. This ChatGPT diagnostic tool has the potential to assist healthcare providers in accurately identifying and classifying various kidney diseases, contributing to timely and effective treatment decisions [35].…”

Section: Development Of Chatgpt Diagnostic Model For Kidney Diseasementioning

confidence: 99%

Innovating Personalized Nephrology Care: Exploring the Potential Utilization of ChatGPT

Miao,

Thongprayoon,

Suppadungsuk

et al. 2023

JPM

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The rapid advancement of artificial intelligence (AI) technologies, particularly machine learning, has brought substantial progress to the field of nephrology, enabling significant improvements in the management of kidney diseases. ChatGPT, a revolutionary language model developed by OpenAI, is a versatile AI model designed to engage in meaningful and informative conversations. Its applications in healthcare have been notable, with demonstrated proficiency in various medical knowledge assessments. However, ChatGPT’s performance varies across different medical subfields, posing challenges in nephrology-related queries. At present, comprehensive reviews regarding ChatGPT’s potential applications in nephrology remain lacking despite the surge of interest in its role in various domains. This article seeks to fill this gap by presenting an overview of the integration of ChatGPT in nephrology. It discusses the potential benefits of ChatGPT in nephrology, encompassing dataset management, diagnostics, treatment planning, and patient communication and education, as well as medical research and education. It also explores ethical and legal concerns regarding the utilization of AI in medical practice. The continuous development of AI models like ChatGPT holds promise for the healthcare realm but also underscores the necessity of thorough evaluation and validation before implementing AI in real-world medical scenarios. This review serves as a valuable resource for nephrologists and healthcare professionals interested in fully utilizing the potential of AI in innovating personalized nephrology care.

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Combining human and AI could predict nephrologies future, but should be handled with care

Cited by 9 publications

References 11 publications

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice

ChatGPT and the Future of Digital Health: A Study on Healthcare Workers’ Perceptions and Expectations

Innovating Personalized Nephrology Care: Exploring the Potential Utilization of ChatGPT

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